Csr Imaging Us, LP

Thomas A Schuneman

Fred William Andree

A system, method, and computer program product are provided for automatically segmenting input document images into regions of black text, white space, and image content. A set of scanned training documents representing the range of text and images to be processed is coarsely tagged to classify regions by content type. The training images are divided into bricks, parameters describing individual brick features are evaluated, and the bricks are classified according to the parameter values. A classification map that relates parameter values to classification codes describing content type is constructed by generating linear equations separating a parameter space into parameter regions along classification boundaries. After training, input documents are scanned and divided into bricks, and brick parameters are converted into an index into the classification map, to classify document regions by content.

Automated segmentation tuner

Systems and methods which provide color conversion using intelligent boundary point perturbation techniques are shown. Embodiments operate to initially select only boundary point indices for indexing data of an input color space to a color space transformation matrix representing the transformation between the input color space and an output color space. A boundary point perturbation process is applied to the initially selected boundary point indices to intelligently alter the boundary point index selections and thereby provide selection of boundary point indices having intelligent boundary point perturbation. Embodiments of the invention utilize an intelligent address generator to selectively apply constraints when indexing the input color space values to boundary points within a color look up table for transforming the input color space values to appropriate output color space values using the boundary point indices provided by the boundary point perturbation process.

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Medford, MA, United States of America

Thomas A Schuneman