Abstract: A system and method in accordance with the present invention includes a scanning assembly and a storage device coupled to a programmed computer with a set of instructions for carrying out an assessment of a document image. The system and method operate by: processing the document image to obtain one or more attributes related to the geometrical integrity of the document image; selecting a threshold value from a database for each of the obtained attributes; and then comparing each of the obtained attributes against the threshold value selected for the obtained attribute to determine a difference for each and then evaluating one or more of the differences using predetermined criteria to provide evaluation results of the geometrical integrity of the document image.

Abstract: The present invention efficiently and quickly estimates signal (code value) dependant noise in an image and subsequently reduces that noise. The digital image is segmented both according to code value and into smooth vs. textured regions. Noise estimates taken from smooth regions are used to model noise as a function of code value. The predictions of the model are used to tone noise reduction in all areas of the image according to the appropriate code value.

Abstract: An automated method and system for digital imaging processing of radiologic images, wherein digital image data is acquired and subjected to multiple phases of digital imaging processing. During the Pre-Processing stage, simultaneous box-rim filtering and k-nearest neighbor processing and subsequent global thresholding are performed on the image data to enhance object-to-background contrast, merge subclusters and determine gray scale thresholds for further processing. Next, during the Preliminary Selection phase, body part segmentation, morphological erosion processing, connected component analysis and image block segmentation occurs to subtract unwanted image data preliminarily identify potentials areas including abnormalities.

Abstract: A method of identifying tissue regions in a digital image representing a body part provides a digital image representing a body part having tissue regions. The digital image is scaled by subsampling or interpolation, and texture extraction is applied to the scaled image to produce a plurality of texture images each having a different measure of the image texture. The texture images are clustered, and the clustered image is labeled based on both pixel intensity values and geometric adjacency of pixels. A threshold is applied to the labeled image, which is then filtered using a largest component filter system to determine the largest geometrically connected region in the threshold image. The filtered image is subjected to edge detection to produce an edge image containing only edge pixels at high code value, and the edge image is operated on to produce a convex hull image which outlines the skin line of the tissue region of the body part provided in the digital image.

Abstract: A method of automatically segmenting the bone regions in a digital radiograph of a body extremity comprising the steps of: providing a digital radiographic image of a body extremity having one or more digits; estimating the upper and lower threshold values of the provided image; binarizing the provided image by a binarization system which uses the estimated upper and lower threshold values to produce a bi-tonal image; removing noise from the binarized image by a noise removal system; processing the noise removed binary image by a skeletonization technique in order to form an initial estimate of the central axis of each body extremity digit; approximating the locus of points generated by the processing step by a linear fit system; joining lines with near end points with a line linking system which results in a piece wise linear approximation of the central axis for each body extremity digit; for each point along the axes, generating perpendicular projections which extend a fixed pixel distance; for each perpen