Thresholding segmentation algorithm based on Otsu criterion and line intercept histogram

Two-dimensional (2-D) Otsu algorithm is analyzed. It is shown that when a 2-D histogram is segmented by 2-D Otsu threshold method, the within-class means is easily far from the main diagonal, so that the algorithm isn't robust enough to noises. This paper proposes a new algorithm. The new algorithm establishes a line intercept histogram directly from the 2-D information of images based on the line threshold segmentation concept. Then, it uses the Otsu criterion to find the best intercept threshold from the histogram. Furthermore, the 2-D information of images and the intercept threshold are adopted to implement the image segmentation. Compared the new algorithm with the 2-D Otsu algorithm, it demonstrates that the new algorithm can avoid both disadvantages of 2-D Otsu algorithm. Firstly, it improves the anti-noise ability. When the noise variance is more than 0.003 or step-up, it shows robustness to noises. Secondly, the processing speed of the new algorithm is faster than the fast Otsu algorithms based on 2-D histogram by two orders of magnitude, and it takes up more less memory. In conclusion, the proposed algorithm is robust anti-noise, more accurate segmentation and is suitable for applications in real time.