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Adaptive uneven illumination correction method of document images.

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Bibliographic Details
Title: Adaptive uneven illumination correction method of document images.
Authors: Fanfeng Zeng1, Shupeng Liu1 13070195207@163.com, Ke Xiao1
Source: Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.). 2017, Vol. 17 Issue 3, p533-544. 12p.
Subjects: Document imaging systems, Adaptive codes, Optical character recognition, Problem solving, Binary number system, Lighting
Abstract: Under condition of uneven illumination, directly recognizing the document image by OCR would lead to a bad effect, which is a difficult point in document recognition. To solve this problem above, a Retinex-based illumination correction method was proposed. Firstly, the images were supposed to be divided into blocks, which were processed respectively by Otsu binarization. The light conditions can be got through the feedback results of processing, which helps to have uneven illumination image blocks achieved. Then images can be enhanced by the improved Retinex method, which extends dynamic range of image block gray value and enhances details of image block. Finally, images can be corrected by sauvola binarization processing. Experimental results show that the algorithm can eliminate the impact of uneven illumination. Compared with the common local binarization and enhancement methods, the OCR recognition rates are significantly increased. At the same time, the combination of global and local methods promotes the applicable scope of being in condition of samples and different illumination. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Under condition of uneven illumination, directly recognizing the document image by OCR would lead to a bad effect, which is a difficult point in document recognition. To solve this problem above, a Retinex-based illumination correction method was proposed. Firstly, the images were supposed to be divided into blocks, which were processed respectively by Otsu binarization. The light conditions can be got through the feedback results of processing, which helps to have uneven illumination image blocks achieved. Then images can be enhanced by the improved Retinex method, which extends dynamic range of image block gray value and enhances details of image block. Finally, images can be corrected by sauvola binarization processing. Experimental results show that the algorithm can eliminate the impact of uneven illumination. Compared with the common local binarization and enhancement methods, the OCR recognition rates are significantly increased. At the same time, the combination of global and local methods promotes the applicable scope of being in condition of samples and different illumination. [ABSTRACT FROM AUTHOR]
ISSN:14727978
DOI:10.3233/JCM-170740