Abstract: A segmentation algorithm for adherent cell images based on edge chain-code information is presented in this paper. Firstly, a pre-processing was carried out for the cell image with low contrast ratio. Then edge chain code of cell binary image was used to keep track of their contours and extract their shape features, such as chain code sum, chain code diff, curvature radius and approximate perimeter. Further, the criterion of distinguishing edge inflexion and sleek curve section was provided. In the end, the adherent cell images were separated through linear interpolation between authentic corners. The presented algorithm has been applied to two sequence images with 120 frames. The segmentation results show that proposed algorithm can not only solve the problem of segmentation but also repair cell edge hollow as well as can count the number of cells successfully. Compared with the threshold algorithm and priori model algorithm, this algorithm can improve the success rate by 40%~60%.