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

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.