Two dimension adaptive threshold segmentation algorithm applied to the segmentation of microscopic cellular image is considered in order to improve the result of segmentation. Based on the characteristic of two dimension histogram of microscopic cellular image and the require of segmentation

one of the two dimension is the pixel's gray value and the other is its neighboring average gray value. usually. at the positions of target or background

gray value of pixel and its neighboring average gray are similar; at the edge of target and background

gray value of pixel and its neighboring average gray are very different

so the pixels of target and background will appear around the diagonal. the sections of the object and the background can being changed

at the same time changing the step's value of searching optimal threshold value

using occur times instead of probability distribution and recursive computation instead of plenty of repeat computation

the improved fast two dimension segmentation algorithms for microscopic cellular image adaptive thresholding segmentation are provided and carried. Simulation shows that the improved algorithms reduces computation complexity greatly and reduces the running time of the algorithms

and the improved algorithms has stronger power against noise and gets clearer edges of targets than original one. From simulation result for cellular image

it could be seen that the improvement and simplification are both valid.