
In this paper, we propose a new binarization method suitable for images having a variety of sizes and degradation levels. It is mainly based on the idea of estimating a document background surface by new smoothing approach through a median filter and compute-Sharp-Peak to replace iterative polynomial. The resulting document image is then segmented by a global threshold binarization. The simulation results confirm that the performance of the proposed method is generally competitive to that of the existing methods. For highly degraded document images, specifically the documents in the BICKLEY DIARY data-base, the performance of the former is substantially better than that of the latter. We show how this approach outperforms the existing and widely used binarization methods in terms of accuracy, F-measure, PSNR, NRM, MPM, DRD, recall and precision.DOI: http://dx.doi.org/10.5755/j01.eie.24.3.20982
Artificial intelligence, Digital Image Stabilization, Shape Matching, Historical document, handwritten and printed documents, thresholding, Optical Image Stabilization, Pattern recognition (psychology), Polynomial, Mathematical analysis, Control Systems and Network Applications, Filter (signal processing), Engineering, Shape Matching and Object Recognition, Image (mathematics), FOS: Mathematics, Data mining, background estimation, Video Stabilization, old documents analysis, histogram analysis, Measure (data warehouse), Computer science, TK1-9971, Algorithm, Control and Systems Engineering, document image analysis, Computer Science, Physical Sciences, Computer vision, Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, Content-Based Image Retrieval, binarization, Digital Video Stabilization Techniques, Mathematics, median filter., Smoothing
Artificial intelligence, Digital Image Stabilization, Shape Matching, Historical document, handwritten and printed documents, thresholding, Optical Image Stabilization, Pattern recognition (psychology), Polynomial, Mathematical analysis, Control Systems and Network Applications, Filter (signal processing), Engineering, Shape Matching and Object Recognition, Image (mathematics), FOS: Mathematics, Data mining, background estimation, Video Stabilization, old documents analysis, histogram analysis, Measure (data warehouse), Computer science, TK1-9971, Algorithm, Control and Systems Engineering, document image analysis, Computer Science, Physical Sciences, Computer vision, Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, Content-Based Image Retrieval, binarization, Digital Video Stabilization Techniques, Mathematics, median filter., Smoothing
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