Multi-threshold image segmentation based on two-dimensional Tsallis

Image multi-threshold segmentation method based on two-dimensional Tsallis entropy is proposed by utilizing Tsallis entropy. The improved particle swarm optimization is used to search best two-dimensional multi-threshold vectors by maximising the two-dimensional Tsallis entropy. The proposed method not only considers the spatial information of pixels, but also the interaction between the object and background, the different responses in variant grey level. The experimental results show that the new algorithm is better than the tradition methods with both a better stability and a higher speed.