  Thresholding is an important task in image processing. It is a main tool in
pattern recognition, image segmentation, edge detection and scene analysis. In
this paper, we present a new thresholding technique based on two-dimensional
Tsallis entropy. The two-dimensional Tsallis entropy was obtained from the
twodimensional histogram which was determined by using the gray value of the
pixels and the local average gray value of the pixels, the work it was applied
a generalized entropy formalism that represents a recent development in
statistical mechanics. The effectiveness of the proposed method is demonstrated
by using examples from the real-world and synthetic images. The performance
evaluation of the proposed technique in terms of the quality of the thresholded
images are presented. Experimental results demonstrate that the proposed method
achieve better result than the Shannon method.
