SPECIFICATION
`
`PATENT
`117313-002UTL
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`Mobile Image Quality Assurance in Mobile Document Image Processing Applications
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`BACKGROUND
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`RELATED APPLICATIONS
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`[0001]
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`The present application is related to U.S. Patent Application No. 12/346,071,
`
`titled
`
`“METHODS
`
`FOR MOBILE IMAGE CAPTURE AND PROCESSING OF
`
`DOCUMENTS” filed on December 30, 2008, U.S. Patent Application No. 12/346,091, titled
`
`“SYSTEMS FOR MOBILE IMAGE CAPTURE AND PROCESSING OF DOCUMENTS” filed
`
`on December 30, 2008, and U.S. Patent Application No. 12/717,080, titled “SYSTEMS FOR
`
`MOBILE IMAGE CAPTURE AND PROCESSING OF CHECKS” filed on March 3, 2010
`
`which are hereby incorporated by reference in their entirety.
`
`BACKGROUND
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`1.
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`Technical Field
`
`[0002]
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`The embodiments described herein relate to processing images of documents
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`captured using a mobile device, and more particularly to techniques for assuring the quality of
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`document images captured by a mobile device to be used in processing the document.
`
`2.
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`Related Art
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`[0003]
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`Banks and other businesses have become increasingly interested in electronic
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`processing of check and other documents in order to expedite processing of these documents.
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`Users can scan a copy of the document using a scanner or copier to create an electronic copy of
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`the document that can be processed instead of routing a hardcopy of the document from one
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`place to another for processing. For example, some banks can process digital images of checks
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`and extract check information from the image needed to process the check without requiring that
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`the physical check by routed throughout the bank for processing.
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`[0004]
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`Mobile phones that incorporate cameras have also become ubiquitous. However,
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`the quality of images captured varies greatly, and many factors can cause images captured using
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`a mobile phone to be of poor quality. Therefore, images captured by mobile phones are often not
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`of sufficiently high quality to be used for electronic processing of documents.
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`SUMMARY
`
`[0005]
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`Systems and methods for assuring the quality of mobile document image captured
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`using a mobile device, such as a mobile phone, are provided. These techniques can be
`
`implemented on a mobile device and can be used to perform various tests to assess the quality of
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`images of documents captured using the mobile device. The tests can be selected based on the
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`type of document that was imaged, the type of mobile application for which the image quality of
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`the mobile image is being assessed, and/or other parameters such as the type of mobile device
`
`and/or the characteristics of the camera of the mobile device that was used to capture the image.
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`In some embodiments, the image quality assurance techniques can be implemented on a remote
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`server, such as a mobile phone carrier’s server or a web server, and the mobile device routes the
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`mobile image to be assessed and optional processing parameters to the remote server processing
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`and the test results can be passed from the remote server to the mobile device.
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`[0006]
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`According to an embodiment, a mobile document image quality assurance system
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`for assessing the quality of mobile document images captured by a mobile device is provided.
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`The system includes a preprocessing module and a test execution module. The preprocessing
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`module is configured to receive a mobile document image captured using a camera of a mobile
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`device and processing parameters for configuring the system for testing the mobile document
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`image, extract a document subimage from the mobile document image, the document subimage,
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`and select one or more mobile image quality assurance tests to be performed on the mobile
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`image based at least in part on the processing parameters. The test execution module is
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`configured to execute the one or more mobile image quality assurance tests on the document
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`subimage to assess the quality of the mobile image, and reject the mobile document image if the
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`image fails at least one mobile image quality test.
`
`[0007]
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`According to another embodiment, a computer-implemented method for assessing
`
`the quality of mobile document images captured by a mobile device is provided. The method
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`includes receiving a mobile document image captured using a camera of a mobile device and
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`processing parameters for configuring the system for testing the mobile document
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`image,
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`extracting a document subimage from the mobile document image, the document subimage,
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`selecting one or more mobile image quality assurance tests to be performed on the mobile image
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`based at least in part on the processing parameters, executing the one or more mobile image
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`quality assurance tests on the document subimage to assess the quality of the mobile image, and
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`rejecting the mobile document image if the image fails at least one mobile image quality test.
`
`[0008]
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`These and other features, aspects, and embodiments are described below in the
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`section entitled “Detailed Description.”
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`BRIEF DESCRIPTION OF THE DRAWINGS
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`[0009]
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`Features, aspects, and embodiments are described in conjunction with the attached
`
`drawings, in which:
`
`[00l0]
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`Fig.
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`l
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`is a high level block diagram of a system for performing mobile image
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`quality assurance according on images captured by a mobile device;
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`[0011]
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`Fig. 2 is a flow diagram of a process for performing mobile image quality
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`assurance on an image captured by a mobile device according to an embodiment;
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`[0012]
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`Fig. 3 is a flow diagram of a process for performing mobile image quality
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`assurance on an image of a check captured by a mobile device according to an embodiment;
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`[0013]
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`Fig.4A is an example of a mobile image captured by a mobile device according to
`
`an embodiment;
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`[0014]
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`Fig. 4B is an example of a snippet generated by a mobile document image
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`processing engine from the mobile image illustrated in Fig. 4A;
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`[0015]
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`Fig. 5A is an example of a mobile image captured by a mobile device according
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`to an embodiment;
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`[0016]
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`Fig. 5B is an example of a blurry mobile image of the document illustrated in Fig.
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`5A according to an embodiment;
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`[0017]
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`Fig. 6 is an example mobile image of a shadowed document according to an
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`embodiment;
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`[0018]
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`Fig. 7 is an example of a mobile image having low contrast according to an
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`embodiment;
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`[0019]
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`Fig. 8 is a method for testing the contrast of a mobile image according to an
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`embodiment;
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`[0020]
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`Fig. 9A is an example of a mobile image of a document having significant plane
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`skew according to an embodiment;
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`[0021]
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`Fig. 9B is an example of a mobile image of a document having view plane skew
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`according to an embodiment;
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`[0022]
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`Fig.
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`l0 is a method for testing the skew of a mobile image according to an
`
`embodiment;
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`[0023]
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`Fig. ll is an example of a mobile image where the comer of the imaged document
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`is cut off according to an embodiment;
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`[0024]
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`Fig. 12 is a method for testing whether one or more comers of a document in a
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`mobile image have been cut off according to an embodiment;
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`[0025]
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`Fig. 13 is an example of a mobile image where the side of the imaged document is
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`cut off according to an embodiment;
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`[0026]
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`Fig. l4 is a method for testing whether a side of a document in a mobile image
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`have been cut off according to an embodiment;
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`[0027]
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`Fig. 15 is an example of a mobile image where the image of the document is
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`warped according to an embodiment;
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`[0028]
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`Fig. l6 is an example method for testing whether a document in a mobile image is
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`warped according to an embodiment;
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`[0029]
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`Fig. 17 is an example of an mobile image where document subimage captured in
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`the mobile image is small compared to the overall size of the mobile document image according
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`to an embodiment;
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`[0030]
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`Fig. 18 is a method for testing whether the size of the image captured in a mobile
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`image is too small;
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`[003 l]
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`Fig. 19 is a method for testing whether a MICR line of the document captured in a
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`mobile image is of high enough quality according to an embodiment;
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`[0032]
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`Fig. 20 is a method for testing the aspect ratios of the front and back images of a
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`check to test whether the images are of the same check according to an embodiment;
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`[0033]
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`Fig. 21 is a method for testing whether the image of the front of the check has
`
`been marked as an image of the back of the check according to an embodiment; and
`
`[0034]
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`Fig. 22 is a block diagram of a computing device on which the mobile image
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`quality assurance system described above can be implemented according to an embodiment.
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`DETAILED DESCRIPTION
`
`[0035]
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`The following detailed description is directed to certain specific embodiments.
`
`However, it will be understood that these embodiments are by way of example only and should
`
`not be seen as limiting the systems and methods described herein to the specific embodiments,
`
`architectures, etc.
`
`In this description, reference is made to the drawings wherein like parts are
`
`designated with like numerals throughout.
`
`[0036]
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`Techniques for assuring the good quality of image (also referred to herein as
`
`“mobile images” or “mobile document images”) taken by cameras on a mobile device, such as a
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`mobile phone, are provided herein.
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`These techniques include a mobile document
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`image
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`processing engine that can select various mobile image quality assurance tests (also referred to
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`herein as “mobile IQA tests”) that can be executed on an image or images of a document
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`captured using a camera of the mobile device. These tests can be configured to ensure that the
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`quality of the mobile document image is sufficient for processing by a mobile application that
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`can process documents captured in an image. The tests are fully configurable and can be
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`configured based on various criteria, such as the type of document being image, the type of
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`mobile device used to capture the image, and/or the type of mobile application for which the
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`mobile document image was captured. If the mobile document image fails one or more tests, the
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`user of the mobile device can be provided with a detailed explanation as to why the mobile
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`document image failed these tests. The detailed explanation can include detailed guidance to
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`assist the user in eliminating or at least minimizing defects in the mobile document image. This
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`guidance can assist the user in capturing a higher quality image of the document with the mobile
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`device.
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`[0037]
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`The mobile image quality assurance systems and methods described herein can be
`
`used to test the quality of Various types of mobile document images, such images of checks,
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`receipts, business, cards, etc. According to an embodiment, specific tests can be developed for
`
`identifying problems with mobile images for specific types of documents. For example, some of
`
`the embodiments describing test methods that can be used with the mobile image quality
`
`assurance system are directed to methods for Verifying the quality of images of checks and can
`
`be used in conjunction with mobile deposit applications to ensure that the quality of images of
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`checks are high enough to be processed by the Mobile Deposit application, such as that described
`
`in related U.S. Patent Application No. 12/346,071 (referred to herein as the “‘071 Application”),
`
`[0038]
`
`U.S. Patent Application No. 12/346,091 (referred to herein as the “‘091
`
`Application”), and U.S. Patent Application No. 12/717,080 (referred to herein as the “’080
`
`Application”). Furthermore, in some embodiments, tests can be performed to determine whether
`
`the correct type of document has been imaged. The test can be configured to fail a mobile
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`document image causing the image to be rejected by the mobile image quality assurance system
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`if the expected type of document is not found. For example, a mobile application might be used
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`to capture an image of a check for processing.
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`If the user instead captures an image of a sales
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`receipt from a store, the test can recognize that the proper type of document for the mobile
`
`application was not imaged.
`
`[0039]
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`According to some embodiments, the mobile image quality assurance system
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`disclosed herein can be integrated with one or more mobile applications that process mobile
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`document images, such as mobile deposit applications for processing images of checks to be
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`deposited into a bank account or contacts or social networking applications where images of
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`business cards can be processed in order to extract
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`information from the business card.
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`According to an embodiment, the mobile application can run on the mobile device and can be
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`integrated to use mobile image quality assurance functionality that is implemented on the mobile
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`device and/or on a remote server. The mobile application can use the mobile image quality
`
`assurance system to assess whether a mobile image is of a high enough quality for processing by
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`the mobile image.
`
`[0040]
`
`Image quality can be impacted by a number of factors. The characteristics of the
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`camera of the mobile device can have a significant impact on the quality of images captured by
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`the mobile device. For example, some characteristics that can affect the quality of images
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`captured using the mobile device include the presence or lack of an auto-focus feature in camera,
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`the presence or lack of a flash in the camera; the image resolution of the camera, i.e., the number
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`of image sensor elements that the camera includes; and the image compression used by the
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`camera for storing the captured images.
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`For example,
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`the use of a high level of image
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`compression can result
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`in degraded image quality depending on how lossy of an image
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`compression technique is applied by the camera.
`
`[0041]
`
`Image quality of images captured by a mobile device can also be affected by
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`numerous environmental factors that depend upon the context in which the image was captured.
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`For example, the location of a document within the camera’s frame or view. The user may not
`
`have centered the document in the frame, the document may be skewed relative to the frame, or
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`both. The position of the camera relative to the document being imaged can also affect the
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`image quality. For example, the angle that the user holds the mobile device relative to the
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`document can affect the quality of the image captured. The location of light sources relative to
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`the camera and/or the document can also greatly affect the quality of the image capture. The
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`exposure time used by the camera when capturing an image of a document can also negatively
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`affect
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`image quality.
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`Furthermore,
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`the color or colors of the background surrounding a
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`document being captured can also affect the image quality.
`
`[0042]
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`As a result of environmental factors, many mobile images of documents have
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`various geometrical defects, such as skewing; warping; cut-off comers or sides of the documents,
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`where a portion of the image was out of frame; as well as such defects as blurriness; shadows;
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`poor contrast; unequal brightness; etc.
`
`[0043]
`
`It is important to note that both camera characteristics and environmental factors
`
`are specific to mobile imaging. These problems simply don’t exist in case of scanned document
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`images.
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`In other words, flat-bed (or transport) scanners generate images which lack the defects
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`mentioned above. Many of the defects described above are eliminated simply by automatic
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`cropping of document image supported by most of flat-bed scanners, or by fixed lighting
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`conditions used in scanners, or by flattening the document under closed scanner lid.
`
`[0044]
`
`A camera’s characteristics are generally fixed, meaning that the user of the mobile
`
`device often does not have the ability alter the configuration of the camera or may only be able to
`
`do so to a very limited extent; however, a user may be able to change some or even most of the
`
`environmental factors that can negatively impact the quality of a mobile image. The mobile
`
`image quality assurance techniques described herein can be used in conjunction with mobile
`
`applications to evaluate mobile images against various thresholds, detect bad images, reject the
`
`bad images, and provide a precise explanation of why the image has been rejected to a user of
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`the mobile device. By informing the user as to what was wrong with a mobile image, the user is
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`much more likely to be able to correct some of factors that contributed to the image being
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`rejected and significantly increase the likelihood that the user will be able to successfully take a
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`high-quality image of the document that can be used by the mobile application.
`
`[0045]
`
`Some problems can be addressed by fixing the problem detected by the mobile
`
`image quality assurance system. For example, if an image is rejected for failing an Image Focus
`
`Image Quality Assurance test, the user may be able to improve the image quality by simply
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`illuminating the document being image with more light, by simply holding the mobile device
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`steadier while taking the picture to avoid motion blur, or both. However, some problems
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`detected by the system cannot be corrected by simply retaking another image of the document.
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`For example, an image of a check can be rejected if the MICR-line on the check cannot be
`
`clearly detected in the image. MICR stands for Magnetic Ink Character Recognition.
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`Information can be printed on the front of a check in a special typeface using a special
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`magnetized ink. A MICR IQA test can use optical character recognition techniques to identify
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`the MICR information on a check.
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`If the MICR line on the front of the check is damaged,
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`simply retaking an image of the check will not correct the defects in the image and the image
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`will be rejected; however, if the MICR line was merely blurry or unreadable due to one or more
`
`of the factors described above, retaking the image after correcting one or more of factors may
`
`result in a high-enough quality image that the MICR line can be read from the check.
`
`[0046]
`
`According to an embodiment, the mobile IQA logic can be dynamically adjusted
`
`“on-the-fly” to avoid repeating the same rejections for a mobile document image. According to
`
`an embodiment, test parameters used by mobile IQA tests can be adjusted to minimize the false
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`reject rate where mobile images are rejected that are of sufficient image quality to be processed
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`by a mobile application and/or the false accept rate of images where the image are accepted that
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`are not of sufficient quality to be processed by a mobile application.
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`Furthermore,
`
`in an
`
`embodiment, tests can be configured for the specific type of mobile device used to capture the
`
`image. For example, different camera phones have cameras with different optics, which can
`
`result in very different image quality. As a result, some image quality defects may be avoidable
`
`on some camera phones but be unavoidable other camera phones. To mitigate the differences
`
`between mobile devices configurations, the mobile IQA tests can be configured for the type of
`
`mobile device that is being used to capture the mobile image.
`
`[0047]
`
`Fig.
`
`1 illustrates a mobile document image processing engine (MDIPE) module
`
`100 for performing quality assurance testing on mobile document images according to an
`
`embodiment. The MDIPE module 100 can receive a mobile document image captured by a
`
`mobile device, or multiple mobile images for some tests; perform preprocessing on the mobile
`
`document image; select tests to be performed on the mobile document image; and execute the
`
`selected tests to determine whether the quality of the image of a high enough quality for a
`
`particular mobile application. The MDIPE module 100 includes a preprocessing module 110 and
`
`test execution module 130. The preprocessing module 110 can be configured to receive a mobile
`
`image 105 captured using a camera of a mobile device as well as processing parameters 107.
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`According to an embodiment, the mobile image 105 and the processing parameters 107 can be
`
`passed to MDIPE 100 by a mobile application on the mobile device where the mobile application
`
`provides the mobile image 105 to the MDIPE 100 to have the quality of the mobile image 105
`
`assessed.
`
`[0048]
`
`The processing parameters 107 can include various information that the MDIPE
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`100 can use to determine which tests to run on the mobile image 105. For example, the
`
`processing parameters 107 can identify the type of device used to capture the mobile image 105,
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`the type of mobile application that will be used to process the mobile image if the mobile image
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`passes the IQA testing, or both. The MDIPE 100 can use this information to determine which
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`tests to select from test data store 132 and which test parameters to select from test parameter
`
`data store 134. For example, if a mobile image is being tested for a mobile deposit application
`
`that expects an image of a check, a specific set of tests related to assessing the image quality for
`
`a mobile image of a check can be selected, such as an MICR-line test, or a test for whether an
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`image is blurry, etc. The MDIPE 100 can also select test parameters from test parameters data
`
`store 134 that are appropriate for the type of image to be processed, or for the type of mobile
`
`device that was used to capture the image, or both.
`
`In an embodiment, different parameters can
`
`be selected for different mobile phones that are appropriate for the type of phone used to capture
`
`the mobile image. For example, some mobile phones might not include an autofocus feature.
`
`[0049]
`
`The preprocessing module 110 can process the mobile document image to extract
`
`a document snippet that includes the portion of the mobile document that actually contains the
`
`document to be processed. This portion of the mobile document image is also referred to herein
`
`as the document subimage. The preprocessing module 110 can also perform other processing on
`
`the document snippet, such as converting the image to a grayscale or bi-tonal document snippet,
`
`geometric correction of the document subimage to remove view distortion, etc. Different tests
`
`can require different types of preprocessing to be performed, and the preprocessing module 110
`
`can produce mobile document snippets from a mobile document image depending on the types of
`
`mobile IQA tests to be executed on the mobile document image.
`
`[0050]
`
`The test execution module 130 receives the selected tests and test parameters 112
`
`and the preprocessed document snippet (or snippets) 120 from the preprocessing mobile 110.
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`The test execution module 130 executes the selected tests on the document snippet generated by
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`the processing engine 130. The test execution module 130 also uses the test parameters provided
`
`by the preprocessing module 110 when executing the test on the document snippet. The selected
`
`tests can be a series of one or more tests to be executed on the document snippets to determine
`
`whether the mobile document image exhibits geometrical or other defects.
`
`[0051]
`
`The test execution module 130 executes each selected test to obtain a test result
`
`value for that test. The test execution module 130 then compares that test result value to a
`
`threshold value associated with the test.
`
`If the test result value is equal to or exceeds the
`
`threshold, then the mobile image has passed the test. Otherwise, if the test result value is less
`
`than the threshold,
`
`the mobile document
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`image has failed the test. According to some
`
`embodiments,
`
`the test execution module 130 can store the test result values for the tests
`
`performed in test results data store 138.
`
`[0052]
`
`According an embodiment, the test threshold for a test can be stored in the test
`
`parameters data store 134 and can be fetched by the preprocessing module 110 and included with
`
`the test parameters 112 provided to the test execution module 130. According to an
`
`embodiment, different
`
`thresholds can be associated with a test based on the processing
`
`parameters 107 received by the preprocessing engine 110. For example, a lower threshold might
`
`be used for an image focus IQA test for image capture by camera phones that do not include an
`
`autofocus feature, while a higher threshold might be used for the image focus IQA test for image
`
`capture by camera phones that do include an autofocus feature.
`
`[0053]
`
`According to an embodiment, a test can be flagged as “affects overall status.”
`
`These tests are also referred to here as “critical” tests. If a mobile image fails a critical test, the
`
`MDIPE 100 rejects the image and can provide detailed information to the mobile device user
`
`explaining why the image was not of a high enough quality for the mobile application and that
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`provides guidance for retaking the image to correct the defects that caused the mobile document
`
`image to fail the test, in the event that the defect can be corrected by retaking the image.
`
`[0054]
`
`According to an embodiment, the test result messages provided by the MDIPE
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`l00 can be provided to the mobile application that requested the MDIPE 100 perform the quality
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`assurance testing on the mobile document image, and the mobile application can display the test
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`results to the user of the mobile device.
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`In certain embodiments, the mobile application can
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`display this information on the mobile device shortly after the user takes the mobile document
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`image to allow the user to retake the image if the image is found to have defects that affect the
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`overall status of the image.
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`In some embodiments, where the MDIPE 100 is implemented at
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`least in part on the mobile device, the MDIPE l00 can include a user interface module that is
`
`configured to display the test results message on a screen of the mobile device.
`
`[0055]
`
`Fig. l merely provides a description of the logical components of the MDIPE l00.
`
`In some embodiments, the MDIPE l00 can be implemented on the mobile device, in software,
`
`hardware, or a combination thereof. In other embodiments, the MDIPE l00 can be implemented
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`on a remote server, and the mobile device can send the mobile image 105 and the processing
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`parameters 107, e.g., via a wireless interface, to the remote server 108 for processing, and the
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`remote server sends the test results and test messages 140 to the mobile device to indicate
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`whether the mobile image passed testing.
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`In some embodiments, part of the functionality of the
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`MDIPE l00 can be implemented on the mobile device while other parts of the MDIPE l00 are
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`implemented on the remote server. The MDIPE l00 can be implemented in software, hardware,
`
`or a combination thereof
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`In still other embodiments, the MDIPE 100 can be implemented
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`entirely on the remote server, and can be implemented using appropriate software, hardware, or a
`
`combination there.
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`[0056]
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`Fig. 2 is a flow diagram of a process for performing mobile image quality
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`assurance on an image captured by a mobile device according to an embodiment. The process
`
`illustrated in Fig. 2 can be performed using the MDIPE 100 illustrated in Fig. l.
`
`[0057]
`
`The mobile image 105 captured by a mobile device is received (step 205). The
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`mobile image 105 can also be accompanied by one or more processing parameters 107.
`
`[0058]
`
`As described above, the MDIPE 100 can be implemented on the mobile device,
`
`and the mobile image can be provided by a camera that is part of or coupled to the mobile
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`device.
`
`In some embodiments, the MDIPE 100 can also be implemented at least in part on a
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`remote server, and the mobile image l05 and the processing parameters 107 can be transmitted
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`to the remove server, e.g., via a wireless interface included in the mobile device.
`
`[0059]
`
`Once the mobile image 105 and the processing parameters 107 have been
`
`received, the mobile image is processed to generate a document snippet or snippets (step 210).
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`For example, preprocessing module 110 of MDIPE 100 can be used to perform various
`
`preprocessing on the mobile image. One part of this preprocessing includes identifying a
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`document subimage in the mobile image. The subimage is the portion of the mobile document
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`image that includes the document. The preprocessing module 110 can also perform various
`
`preprocessing on the document subimage to produce what is referred to herein as a “snippet.”
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`For example, some tests can require that a grayscale image of the subimage be created. The
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`preprocessing module 110 can create a grayscale snippet that represents a grayscale version of
`
`the document subimage.
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`In another example, some tests can require that a bitonal image of the
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`subimage be created. The preprocessing module 110 can create a bitonal snippet that represents
`
`a bitonal version of the document subimage.
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`In some embodiments, the MDIPE 100 can
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`generate multiple different snippets based on the types of tests to be performed on the mobile
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`document image.
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`[0060]
`
`After processing the mobile document image to generate a snippet, the MDIPE
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`100 then selects one or more tests to be performed on the snippet or snippets (step 215).
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`In an
`
`embodiment,
`
`the tests to be performed can be selected from test data store 132.
`
`In an
`
`embodiment, the MDIPE 100 selects the one or more tests based on the processing parameters
`
`107 that were received with the mobile image 105.
`
`[0061]
`
`After selecting the tests from the test data store 132, test parameters for each of
`
`the tests can be selected from the test parameters data store 134 (step 220). According to an
`
`embodiment, the test parameters can be used to configure or customize the tests to be performed.
`
`For example, different test parameters can be used to configure the tests to be more or less
`
`sensitive to certain attributes of the mobile image.
`
`In an embodiment, the test parameters can be
`
`selected based on the processing parameters 107 received with the mobile image 105. As
`
`described above, these processing parameters can include information, such as the type of mobile
`
`device used to capture the mobile image as well as the type of mobile application that is going to
`
`be used to process the mobile image if the mobile image passes scrutiny of the mobile image
`
`IQA system.
`
`[0062]
`
`Once the tests and the test parameters have been retrieved and provided to the test
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`execution module 130, a test is selected from tests to be executed, and the test is executed on the
`
`document snippet to produce a test result value (step 225). In some embodiments, more than one
`
`document snippet may be used by a test. For example, a test can be performed that tests whether
`
`images of a front and back of a check are actually images of the same document can be
`
`performed. The test engine can receive both an image of the front of the check and an image of
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`the back of the check fiom the preprocessing engine 110 and use both of these images when
`
`executing the test.
`
`[0063]
`
`The test result value obtained by executing the test on the snippet or snippets of
`
`the mobile document is then compared to test threshold to determine whether the mobile image
`
`passes or fails the test (step 230) and a determination is made whether the test results exceed the
`
`threshold (step 235). According to an embodiment, the test threshold can be configured or
`
`customized based on the processing parameters 107 received wi