Abstract: Various embodiments disclosed herein are directed to methods of capturing Vehicle Identification Numbers (VIN) from images captured by a mobile device. Capturing VIN data can be useful in several applications, for example, insurance data capture applications. There are at least two types of images supported by this technology: (1) images of documents and (2) images of non-documents.

Abstract: Techniques for assuring the quality of mobile document image captured using a mobile device are provided. These techniques include performing one or more tests to assess the quality of images of documents captured using the mobile device. The tests can be selected based on the type of document that was imaged, the type of mobile application for which the image quality of 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. The image quality assurance techniques can also be implemented on can be implemented on a mobile device and/or on a remote server where the mobile device routes the mobile image to the remote server processing and the test results are be passed from the remote server to the mobile device.

Abstract: Systems and methods are provided for assessing whether mobile deposit processing engines meet specified standards for mobile deposit of financial documents. A mobile deposit processing engine (MDE) is evaluated to determine if it can perform technical capabilities for improving the quality of and extracting content from an image of a financial document. A verification process then begins, where the MDE performs the image quality enhancements and text extraction steps on sets of images from a test deck. The results of the processing of the test deck are then evaluated by comparing confidence levels with thresholds to determine if each set of images should be accepted or rejected. Further analysis determines whether any of the sets of images were falsely accepted or rejected in error. An overall error rate is then compared with minimum accuracy criteria, and if the criteria are met, the MDE meets the standard for mobile deposit.

Abstract: Various embodiments disclosed herein are directed to methods of capturing Vehicle Identification Numbers (VIN) from images captured by a mobile device. Capturing VIN data can be useful in several applications, for example, insurance data capture applications. There are at least two types of images supported by this technology: (1) images of documents and (2) images of non-documents.

Abstract: Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the document, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the document, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

Abstract: Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the DL, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the DL, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

Abstract: Methods and systems are provided for defining and determining a formal and verifiable mobile document image quality and usability (MDIQU) standard, or Standard for short. The Standard ensures that a mobile image can be used in an appropriate mobile document processing application, for example an application for mobile check deposit. In order to quantify the usability, the Standard establishes 5 quality and usability grades. A mobile image capture device can capture images. A mobile device can receive information associated with one or more image quality assurance (IQA) criteria; evaluating the images to select an image satisfying an image quality criteria based on the received information; and in response to the image satisfying the image quality score, sending the selected image to determine a set of image quality assurance (IQA) scores.

Abstract: Various embodiments disclosed herein are directed to methods of capturing Vehicle Identification Numbers (VIN) from images captured by a mobile device. Capturing VIN data can be useful in several applications, for example, insurance data capture applications. There are at least two types of images supported by this technology: (1) images of documents and (2) images of non-documents.

Abstract: Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the DL, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the DL, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

Abstract: Methods are provided for defining and determining a formal and verifiable mobile document image quality and usability (MDIQU) standard, or Standard for short. The Standard ensures that a mobile image can be used in an appropriate mobile document processing application, for example an application for mobile check deposit. In order to quantify the usability, the Standard establishes 5 quality and usability grades. A mobile image is first tested to determine if the quality is sufficient to obtain content from the image by performing multiple different image quality assessment tests. If the image quality is sufficient, one or more document usability computations are made to determine if the document or content in the image is usable by a particular application. A ranking is then assigned to the image based on the results of the tests which is indicative of the quality and usability of the image.

Abstract: Techniques for assuring the quality of mobile document image captured using a mobile device are provided. These techniques include performing one or more tests to assess the quality of images of documents captured using the mobile device. The tests can be selected based on the type of document that was imaged, the type of mobile application for which the image quality of 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. The image quality assurance techniques can also be implemented on can be implemented on a mobile device and/or on a remote server where the mobile device routes the mobile image to the remote server processing and the test results are be passed from the remote server to the mobile device.

Abstract: Various embodiments disclosed herein are directed to methods of capturing Vehicle Identification Numbers (VIN) from images captured by a mobile device. Capturing VIN data can be useful in several applications, for example, insurance data capture applications. There are at least two types of images supported by this technology: (1) images of documents and (2) images of non-documents.

Abstract: Systems and methods are provided for processing and extracting content from an image of a driver's license captured using a mobile device. In one embodiment, an image of a driver's license (DL) is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by cropping the image, identifying the format and layout of the DL, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image cropping may be implemented to accurately assess the borders of the DL, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

Abstract: Techniques for assuring the quality of mobile document image captured using a mobile device are provided. These techniques include performing one or more tests to assess the quality of images of documents captured using the mobile device. The tests can be selected based on the type of document that was imaged, the type of mobile application for which the image quality of 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. The image quality assurance techniques can also be implemented on can be implemented on a mobile device and/or on a remote server where the mobile device routes the mobile image to the remote server processing and the test results are be passed from the remote server to the mobile device.

Abstract: Methods are provided for defining and determining a formal and verifiable mobile document image quality and usability (MDIQU) standard, or Standard for short. The Standard ensures that a mobile image can be used in an appropriate mobile document processing application, for example an application for mobile check deposit. In order to quantify the usability, the Standard establishes 5 quality and usability grades. A mobile image is first tested to determine if the quality is sufficient to obtain content from the image by performing multiple different image quality assessment tests. If the image quality is sufficient, one or more document usability computations are made to determine if the document or content in the image is usable by a particular application. A ranking is then assigned to the image based on the results of the tests which is indicative of the quality and usability of the image.

Abstract: The embodiments herein focus on improving recognition accuracy of these fields on credit card bills by detecting and identifying critical fields on a credit card, extracting the data from the critical fields and comparing the data with known data on a payor, payee and biller.

Abstract: Methods are provided for defining and determining a formal and verifiable mobile document image quality and usability (MDIQU) standard, or Standard for short. The Standard ensures that a mobile image can be used in an appropriate mobile document processing application, for example an application for mobile check deposit. In order to quantify the usability, the Standard establishes 5 quality and usability grades. A mobile image is first tested to determine if the quality is sufficient to obtain content from the image by performing multiple different image quality assessment tests. If the image quality is sufficient, one or more document usability computations are made to determine if the document or content in the image is usable by a particular application. A ranking is then assigned to the image based on the results of the tests which is indicative of the quality and usability of the image.

Abstract: Systems and methods are provided for processing and extracting content from an image of a driver's license captured using a mobile device. In one embodiment, an image of a driver's license (DL) is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by cropping the image, identifying the format and layout of the DL, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image cropping may be implemented to accurately assess the borders of the DL, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

Abstract: Techniques for assuring the quality of mobile document image captured using a mobile device are provided. These techniques include performing one or more tests to assess the quality of images of documents captured using the mobile device. The tests can be selected based on the type of document that was imaged, the type of mobile application for which the image quality of 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. The image quality assurance techniques can also be implemented on can be implemented on a mobile device and/or on a remote server where the mobile device routes the mobile image to the remote server processing and the test results are be passed from the remote server to the mobile device.

Abstract: Systems and methods are provided for processing an image of a financial payment document captured using a mobile device and classifying the type of payment document in order to extract the content therein. These methods may be implemented on a mobile device or a central server, and can be used to identify content on the payment document and determine whether the payment document is ready to be processed by a business or financial institution. The system can identify the type of payment document by identifying features on the payment document and performing a series of steps to determine probabilities that the payment document belongs to a specific document type. The identification steps are arranged starting with the fastest step in order to attempt to quickly determine the payment document type without requiring lengthy, extensive analysis.