Abstract
This paper presents a technique for extracting the user-entered information from bankcheck images based on a layout-driven item extraction method. The baselines of checks are detected and eliminated by using gray-level mathematical morphology. A priori information about the positions of data is integrated into a combination of top-down and bottom-up analyses of check images. The handwritten information is extracted by a local thresholding technique and the information lost during baseline elimination is restored by mathematical morphology with dynamic kernels. A goal-directed evaluation of the extraction approaches is proposed, and both qualitative and quantitative analyses show noticeable advantages of the proposed approach over the existing approaches.
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