%0 Journal Article %A YANG Huixian1 %A YAN Wei2 %A TAN Zhenghua2 %A LI Miao1 %A CAI Yongyong1 %T Improvement image segmentation based on average gray level- local variance two dimensional histogram %D 2017 %R 10.3778/j.issn.1002-8331.1506-0231 %J Computer Engineering and Applications %P 209-213 %V 53 %N 4 %X In view of the obvious shortage of several segmentation methods, such as the gray-the average gray level 2D histogram method, the average gray level-gradient method and 2D histogram oblique segmentation, which are low region homogeneity, low region contrast, and cannot segment accurately enough under the influence of high intensity Gauss noise. This paper proposes a method of maximum between-cluster variance correlation of average gray level-local variance 2D histogram, which uses local variance that not only takes the discrete degree of each pixel point and the center of pixel points into consideration, but also decreases the influence affected by noise. This paper uses a fast recursion algorithm to reduce the amount of calculation. The experimental results show that the method is better than the gray-the average gray level method and the average gray level-gradient method, and has more accurate segmentation results, higher region contrast, region homogeneity, and better anti-noise property. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1506-0231