Abstract
Image binarization refers to convert gray-level images into binary ones, and many binarization algorithms have been developed. The related algorithms can be classified as either high quality computation or high speed performance. This paper presents an algorithm that ensures both benefits at the same time. The proposed algorithm intelligently segments input images into several different sized sub-images by using a Sobel like matrix. After which each sub-image will be classified into background set or foreground set according to it’s feature. Finally the foreground set sub-images will be binarized by Otsu’s method independently. Experimental results reveal that our algorithm provides the appropriate quality with the medium speed.
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References
Beucher S (1994) Watershed, hierarchical segmentation and waterfall algorithm.. In: Mathematical morphology and its applications to image processing, Springer, pp 69–76
Cheriet M, Said J, Suen C (1995) A formal model for document processing of business forms. In: Proceedings of the Third International Conference on Document Analysis and Recognition, vol 1, pp 210–213
Chiu Y-H, Chung K-L, Yang W-N, Huang Y-H, Liao C-H (2012) Parameter-free based two-stage method for binarizing degraded document images. Pattern Recog 45(12):4250–4262
Hegt H, Haye R, Khan N (1998) A high performance license plate recognition system. IEEE Int Conf Syst Man Cybern 5:4357–4362
Manousakas I, Undrill P, Cameron G, Redpath T (1998) Split-and-merge segmentation of magnetic resonance medical images: performance evaluation and extension to three dimensions. Comput Biomed Res 31(6):393–412
Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern SMC-9:62–66
Pai Y-T, Chang Y-F, Ruan S-J (2010) Adaptive thresholding algorithm: Efficient computation technique based on intelligent block detection for degraded document images. Pattern Recog 43(9):3177–3187
Suen CY, Lam L, Guillevic D, Strathy NW, Cheriet M, Said JN, Fan R (1996) Bank check processing system. Int J Imaging Syst Technol 7(4):392–403
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Hung, CS., Ruan, SJ. Efficient adaptive thresholding algorithm for in-homogeneous document background removal. Multimed Tools Appl 75, 1243–1259 (2016). https://doi.org/10.1007/s11042-014-2366-7
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DOI: https://doi.org/10.1007/s11042-014-2366-7