In this paper

a new two-dimensional(2D) thresholding method is proposed in order to improve the efficiency of image segmentation.Based on the characteristic of two-dimensional histogram of image and the requirement of segmentation

one of the two dimensions is the pixel's gray value and the other is its neighboring average gray value.The proposed method utilizes the important edge histogram of the image to segment it

while based on the traditional two-dimensional(2D) Otsu thresholding algorithm.According to the foreknowledge about the relationship of the edge pixel histogram and the threshold vector(s

t)

the proposed method derives the optimal threshold vector(s_best

t_best)

by looking for the valley value existing between two peaks in the edge histogram.Emulational experiments show that

compared with the traditional two-dimensional(2D) Otsu algorithm

the presented method reduces computation complexity greatly and reduces the running time of the algorithms

while retains the advantage of the traditional two-dimensional(2D) OTSU algorithm

such as nonparametric

unsupervised

high performing quality and so on.It can be seen from the emulational result of cellular images that both the improvement and real-time quality of the proposed method are valid.