Aiming at the problem that the edge contour extracted by the traditional edge detection operator,the Canny algorithm, is prone to produce such as redundant contour or edge contour defect, which can not meet the requirements of further research by computer vision, an edge detection algorithm is put forward and applied to the morphological study of cephalopod beak in this text. The algorithm realizes edge detection through five steps, including gray processing, filtering, binarization, constructing target connected domain and extracting edge contour. The results show that using this algorithm for edge detection can effectively distinguish signal and noise, improve the accuracy of target selection, and ensure the integrity of contour within the allowable range of error. It has a good effect in the recognition of cephalopod beak, and the pixel accuracy can reach 97.79%. Compared with the results of Canny algorithm, the results of the improved algorithm are intuitive, complete and more accurate, which provides a new idea for the study of biological morphological characteristics such as beaks of cephalopods.