Fast incremental algorithm for speeding up the computation of binarization |
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Authors: | Kuo-Liang Chung Chia-Lun Tsai |
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Institution: | Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC |
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Abstract: | Binarization is an important basic operation in image processing community. Based on the thresholded value, the gray image can be segmented into a binary image, usually consisting of background and foreground. Given the histogram of input gray image, based on minimizing the within-variance (or maximizing the between-variance), the Otsu method can obtain a satisfactory binary image. In this paper, we first transfer the within-variance criterion into a new mathematical formulation, which is very suitable to be implemented in a fast incremental way, and it leads to the same thresholded value. Following our proposed incremental computation scheme, an efficient heap- and quantization-based (HQ-based) data structure is presented to realize its implementation. Under eight real gray images, experimental results show that our proposed HQ-based incremental algorithm for binarization has 36% execution-time improvement ratio in average when compared to the Otsu method. Besides this significant speedup, our proposed HQ-based incremental algorithm can also be applied to speed up the Kittler and Illingworth method for binarization. |
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Keywords: | Binarization Heap Incremental algorithm Kittler and Illingworth method Otsu method Quantization Within-variance |
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