Abstract: A system for mapping and tracking at least one mole on a surface of a body comprises: an optical system configured to scan a surface of the body and to generate at least one image of at least a portion of the surface and including at least one primary imaging device attachable to at least one first maneuvering mechanism and a switching mechanism in mechanical communication with the at least one optical system. The switching mechanism is configured to reversibly switch the at least one optical system between generating the at least one image of a standing patient and generating the at least one image of a patient lying down.

Abstract: Method, system, and computer program product for tracing seismic sections to convert to digital format are provided. The method includes: receiving a scan of a seismic section having multiple overlapping traces measured at spot points; splitting the traces into segments; associating the segments with appropriate baselines; estimating the traces between segments using logical rules; and deriving amplitudes of the traces.

Abstract: A computer-implemented method for form generation includes capturing an image of a hard-copy form, and automatically processing the image to identify form fields in the image and text characters associated with each of the form fields. Geometrical coordinates of the form fields that define respective filling areas for entry of information into the fields are determined. Optical character recognition (OCR) is applied to the text characters in order to identify form field names. Associations are determined between the form field names and object names of corresponding data objects. The geometrical coordinates of the filling areas of the form fields are combined with the object names of the data objects corresponding to the form fields to generate a form definition.

Abstract: Method, system, and computer program product for tracing seismic sections to convert to digital format are provided. The method includes: receiving a scan of a seismic section having multiple overlapping traces measured at spot points; splitting the traces into segments; associating the segments with appropriate baselines; estimating the traces between segments using logical rules; and deriving amplitudes of the traces.

Abstract: A computer-implemented method for form generation includes capturing an image of a hard-copy form, and automatically processing the image to identify form fields in the image and text characters associated with each of the form fields. Geometrical coordinates of the form fields that define respective filling areas for entry of information into the fields are determined. Optical character recognition (OCR) is applied to the text characters in order to identify form field names. Associations are determined between the form field names and object names of corresponding data objects. The geometrical coordinates of the filling areas of the form fields are combined with the object names of the data objects corresponding to the form fields to generate a form definition.

Abstract: Text is extracted from a grayscale or color compound digital image. Kernels of text in the compound digital image are found using a stroke operator. The kernels of text are segmented into text blocks based on image space, color space, and intensity space. Each text block is segmented into text and background pixels using active contour analysis. The segmented text blocks are refined by altering parameters in the active contour analysis. Text is extracted from the refined segmented text blocks, and a binary image is created including text extracted from the refined segmented text blocks.

Abstract: A method for providing recognition error correction information, the method includes: obtaining metadata associated with a capture of a media item; and generating recognition error correction information in response to the metadata. The recognition error correction information is to be used in a recognition process selected out of a list consisting of an automatic speech recognition process and an optical characters recognition process.

Abstract: A method for generating object information, the method includes: acquiring a representation of an object; acquiring contextual information; and processing the representation of the object and the contextual information to provide object information that includes indexing information.

Abstract: A system and method for determining the validity of a check, the method including receiving from a payer an image of a check to a payee together with a personal identifier identifying the payer, where the payer is a customer of a financial institution, determining an account to which the check pertains, comparing the received personal identifier with a personal identifier maintained by the financial institution for the account, comparing the payer check image with an image of the check produced after the payee receives the check from the payer, designating the check as valid if the personal identifiers are the same and if the check images match within a predefined tolerance, and designating the check as invalid if the personal identifiers are not the same or if the check images do not match within a predefined tolerance.

Abstract: A method for segmentation of characters in text that segments text into lines, words and slices and determines at least one of fixed pitch and proportional pitch prior to segmentation. The method computes histograms of the lines and defines widths of lobes of the histograms of the lines as the character pitches. In addition, the method further analyzes the character pitches; segments lines into words; computes histograms of the words and aggregating the histograms of the words at predetermined points. Moreover, the method segments the words; slicing them words into an upper slice and lower slice and further segments the upper slice and the lower slice. The results are then combined to provide for both coarse and fine segmentation that enhance the performance of character OCR for documents scanned as at least one of gray-scale images and color images.

Abstract: A method for computerized processing of paper forms includes receiving an electronic image of a paper form containing text information from a client having a telephone. The text information is extracted from the form using an optical character recognition (OCR) process. A field of the extracted text information that is suspected of containing an error is identified, and a first text message is automatically communicated to the telephone asking the client to verify the identified field. A second text message is received in response to the first text message, and the text information in the field is validated or corrected according to the response.

Abstract: A method for image separation of an image, wherein the image includes pixels, and the method includes identifying kernels, whereby characteristics of the kernels are reflected by at least one of the following operators, P(x?w,y)?P(x,y)>t AND P(x+w, y)?P(x,y)>t; or P(x, y?w)?P(x,y)>t AND P(x, y+w)?P(x,y)>t; or P(x+d, y+d)?P(x,y)>t AND P(x?d, y?d)?P(x,y)>t; or P(x?d, y+d)?P(x,y)>t AND P(x+d, y?d)?P(x,y)>t, wherein the kernels include at least some of a first group of the pixels. The kernels are associated with a first layer, and pixels that are not associated with the first layer are classified as a second layer. The first layer may be text or graphics and the second layer may be a background. The first layer may be compressed with a high resolution compression technique and the second layer may be compressed with a high lossy compression technique.

Abstract: A method for computerized processing of paper forms includes receiving an electronic image of a paper form containing text information from a client having a telephone. The text information is extracted from the form using an optical character recognition (OCR) process. A field of the extracted text information that is suspected of containing an error is identified, and a first text message is automatically communicated to the telephone asking the client to verify the identified field. A second text message is received in response to the first text message, and the text information in the field is validated or corrected according to the response.

Abstract: A method for locating symbols arranged in one or more rows in an image includes smearing the image, and fitting line segments through edge points of features in the smeared image. A group is found of the line segments that are in mutual proximity and are mutually substantially parallel. A region of the image that contains the group of the line segments is identified as a possible location of the symbols.

Abstract: A method for locating a barcode in an image includes dividing the image into a plurality of tiles, and scanning each of the tiles so as to detect a pattern of stripes associated with the barcode in at least one of the tiles. The pattern of stripes is analyzed so as to determine an angle of orientation of the barcode. Responsive to the determined angle, bounds of the barcode are defined in alignment with the pattern of the stripes.

Abstract: A method for deskewing text is disclosed, in which a noisy digitized gray scale image is preprocessed by binarization, noise removal, and then by smearing in three patterns. A selected smeared image having minimal runs is sampled, and the resulting sampled image subjected to the Hough process using a search technique at two angular resolutions. A dominant text line is chosen from the output of the Hough process, and the image deskewed accordingly. The method is suitable for detecting skew at any angle, and is capable of detecting multiple skew text lines.

Abstract: A method for image separation of an image, wherein the image includes pixels, and the method includes identifying kernels, whereby characteristics of the kernels are reflected by at least one of the following operators, P(x−w,y)−P(x,y)>t AND P(x+w, y)−P(x,y)>t; or P(x, y−w)−P(x,y)>t AND P(x, y+w)−P(x,y)>t; or P(x+d, y+d)−P(x,y)>t AND P(x−d, y−d)−P(x,y)>t; or P(x−d, y+d)−P(x,y)>t AND P(x+d, y−d)−P(x,y)>t, wherein the kernels include at least some of a first group of the pixels. The kernels are associated with a first layer, and pixels that are not associated with the first layer are classified as a second layer. The first layer may be text or graphics and the second layer may be a background. The first layer may be compressed with a high resolution compression technique and the second layer may be compressed with a high lossy compression technique.

Abstract: A method for finding a predefined object in an image includes selecting a line belonging to the object, the line having a known stroke width and defining a maximum width and a minimum width that together define a range of widths therebetween that contains the stroke width. A feature in the image is found having a feature width within the range, and the feature is processed to determine whether it is a part of the object.

Abstract: A method for locating symbols arranged in one or more rows in an image includes smearing the image, and fitting line segments through edge points of features in the smeared image. A group is found of the line segments that are in mutual proximity and are mutually substantially parallel. A region of the image that contains the group of the line segments is identified as a possible location of the symbols.

Abstract: A method for locating a barcode in an image includes dividing the image into a plurality of tiles, and scanning each of the tiles so as to detect a pattern of stripes associated with the barcode in at least one of the tiles. The pattern of stripes is analyzed so as to determine an angle of orientation of the barcode. Responsive to the determined angle, bounds of the barcode are defined in alignment with the pattern of the stripes.