Image Thresholding Based on 2-D Histogram θ-Division and Minimum Error

Abstract

Abstract: Aiming at the problem of wrong segmentation in common 2-D histogram region division, in order to meet the requirement of different images and segmentation objectives, the 2-D linear-type minimum error threshold segmentation method was generalized, and a much more widely suitable thresholding method was proposed based on 2-D histogram θ-division and minimum error. The threshold selection formulae and its fast recursive algorithm were deduced. The influence of different θ values on segmented results and running time was analyzed according to the experimental results. Compared with the conventional 2-D minimum error method, the proposed method not only achieves more accurate segmented result and more robust anti-noise, but also significantly reduces the running time. The linear-type minimum error threshold segmentation method is only a special case with θ=45° of the proposed method.

Key words: image processing, thresholding, 2-D histogram region θdivision, minimum error, recursive algorithm

CLC Number:

WU Yi-Quan-1, 2 , ZHANG Xiao-Jie-1, WU Shi-Hua-1, ZHANG Guo-Hua-2, ZHANG Sheng-Wei-2, YU Su-Fen-2. Image Thresholding Based on 2-D Histogram θ-Division and Minimum Error[J]. Journal of Shanghai Jiaotong University, 2012, 46(06): 892-899.

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