Abstract: Described is an invention that provides methods to identify key features from magnetic image captures of complex magnetic fields of randomly positioned and oriented magnetized particles in an object. The key features are described in a compact form to generate a unique identifier that services as a “fingerprint” of a chip.

Abstract: A mobile device with camera automatically captures an image of a check from a video sequence. A computing application assesses quality metrics of a frame of the video and, if acceptable, initiates capture of the check in that frame without user selection. Metrics include an aspect ratio of the check, image quality of the routing transit symbols that delineate a routing transit number on a MICR line of the check, distances between the routing transit symbols and to an edge of the check, recognition of digits of the routing transit number, checksum of the routing transit numbers, and image sharpness. Other embodiments note cropping of the check from the background of the image, properly orienting the check for viewing, and providing color coded visual feedback to users about the quality of the image frame about the check, to name a few.

Abstract: A system and methods for selecting a region of pixels in an image displayed on a touch-sensitive interface is disclosed. The method for selecting the region of pixels is based on determined connectivity of pixels in the image indicating content of the image and includes determining connected pixels on the image representing the content without performing character recognition, detecting a text selection gesture indicative of selecting the region in the image, determining coordinates of the text selection gesture performed on the touch-sensitive interface and selecting the region in the image by bounding a first set of pixels located at a proximity from the coordinates of the text selection gesture.

Abstract: A mobile device with camera automatically captures an image of a check from a video sequence. A computing application assesses quality metrics of a frame of the video and, if acceptable, initiates capture of the check in that frame without user selection. Metrics include an aspect ratio of the check, image quality of the routing transit symbols that delineate a routing transit number on a MICR line of the check, distances between the routing transit symbols and to an edge of the check, recognition of digits of the routing transit number, checksum of the routing transit numbers, and image sharpness. Other embodiments note cropping of the check from the background of the image, properly orienting the check for viewing, and providing color coded visual feedback to users about the quality of the image frame about the check, to name a few.

Abstract: A system and methods for selecting a region of pixels in an image displayed on a touch-sensitive interface is disclosed. The method for selecting the region of pixels is based on determined connectivity of pixels in the image indicating content of the image and includes determining connected pixels on the image representing the content without performing character recognition, detecting a text selection gesture indicative of selecting the region in the image, determining coordinates of the text selection gesture performed on the touch-sensitive interface and selecting the region in the image by bounding a first set of pixels located at a proximity from the coordinates of the text selection gesture.

Abstract: Systems and methods search pixels of source images and compare them to pixels of templates. Best matches correlate to objects in the image. That environmental conditions impact the appearance of objects, best matching scores suffer under poor lighting and other adverse conditions. Improving scores includes augmenting traditional correlation techniques with object features extracted from the source image and matching them to templates corresponding to the features. Certain embodiments contemplate corrupting pixels of image templates corresponding to objects with pixels extracted from the source image corresponding to features. Representative features include corners, edges, ridges, points/regions of interest, etc. Other embodiments note augmented correlation as a computing application and computing devices therefore, including cameras for capturing images and displaying results to users.

Abstract: A mobile device with camera automatically captures an image of a check from a video sequence. A computing application assesses quality metrics of a frame of the video and, if acceptable, initiates capture of the check in that frame without user selection. Metrics include an aspect ratio of the check, image quality of the routing transit symbols that delineate a routing transit number on a MICR line of the check, distances between the routing transit symbols and to an edge of the check, recognition of digits of the routing transit number, checksum of the routing transit numbers, and image sharpness. Other embodiments note cropping of the check from the background of the image, properly orienting the check for viewing, and providing color coded visual feedback to users about the quality of the image frame about the check, to name a few.

Abstract: A mobile device with camera automatically captures an image of a check from a video sequence. A computing application assesses quality metrics of a frame of the video and, if acceptable, initiates capture of the check in that frame without user selection. Metrics include an aspect ratio of the check, image quality of the routing transit symbols that delineate a routing transit number on a MICR line of the check, distances between the routing transit symbols and to an edge of the check, recognition of digits of the routing transit number, checksum of the routing transit numbers, and image sharpness. Other embodiments note cropping of the check from the background of the image, properly orienting the check for viewing, and providing color coded visual feedback to users about the quality of the image frame about the check, to name a few.

Abstract: Systems and methods search pixels of source images and compare them to pixels of templates. Best matches correlate to objects in the image. That environmental conditions impact the appearance of objects, best matching scores suffer under poor lighting and other adverse conditions. Improving scores includes augmenting traditional correlation techniques with object features extracted from the source image and matching them to templates corresponding to the features. Certain embodiments contemplate corrupting pixels of image templates corresponding to objects with pixels extracted from the source image corresponding to features. Representative features include corners, edges, ridges, points/regions of interest, etc. Other embodiments note augmented correlation as a computing application and computing devices therefore, including cameras for capturing images and displaying results to users.

Abstract: A method of identifying one or more image features of an image based on content of the image according to one example embodiment includes receiving an image, correcting a distortion and a tone of the image, segmenting the corrected image and extracting the one or more image features, generating an input image descriptor based on the one or more extracted image features, matching the input image descriptor with a reference image descriptor, and performing an action based on the matched reference image descriptor.

Abstract: A method of cropping an image based on a content of the image according to one example embodiment includes identifying image features in the content of the image, determining horizontal histogram frequencies and vertical histogram frequencies of the identified image features, determining borders of a document bounding box based on the determined horizontal histogram frequencies and vertical histogram frequencies, and cropping the image according to the document bounding box.

Abstract: A method of identifying one or more image features of an image based on content of the image according to one example embodiment includes receiving an image, correcting a distortion and a tone of the image, segmenting the corrected image and extracting the one or more image features, generating an input image descriptor based on the one or more extracted image features, matching the input image descriptor with a reference image descriptor, and performing an action based on the matched reference image descriptor.

Abstract: A method of cropping an image based on a content of the image according to one example embodiment includes identifying image features in the content of the image, determining horizontal histogram frequencies and vertical histogram frequencies of the identified image features, determining borders of a document bounding box based on the determined horizontal histogram frequencies and vertical histogram frequencies, and cropping the image according to the document bounding box.

Abstract: Disclosed is a method for compensating an imaging defect in an image forming apparatus. The method includes generating a raster image. Further, the method includes determining a compensating profile representing the imaging defect in the image forming apparatus. Furthermore, the method includes forming a defect-compensated image based on the raster image and the compensating profile. Also, disclosed is the image forming apparatus capable of compensating the imaging defect thereof.

Abstract: A scanner calibration strip medium is described which includes at least one of a plurality of text symbols and a plurality of halftoned non-text images. A scanner is described which includes a scan bar and a scanner calibration strip medium scannable by the scan bar. The calibration strip medium includes a plurality of text symbols having text pixels and a plurality of halftoned non-text images having halftoned non-text pixels. A method for segmenting a scanned document image into text symbols and halftoned non-text images is described which uses a scanner calibration strip medium which includes a plurality of text symbols having text pixels and a plurality of halftoned non-text symbols having halftoned non-text pixels, wherein the calibration strip medium has a known pixel classification including which pixels of the calibration strip medium are text pixels and which pixels of the calibration strip medium are halftoned non-text pixels.