Edge Detection and Quantitative Analysis Based on Binary Mathematical Morphology and Its Application to Signature Recognition

Mathematical morphology has a rigorous theoretical basis and concise ideas. It is widely applicable to various aspects of image processing. Edge detection plays a vital role in image analysis, and binary morphology offers a simple yet efficient approach to handling such tasks. This paper applies five different morphological edge detection operators to binary images. It uses Structural Similarity (SSIM), Edge Preservation Index (EPI) and edge pixel error rate to evaluate the experimental results and obtain the optimal morphological edge detection operator. Furthermore, the operator is applied to the signature recognition system. The results show that the operator can effectively extract the edges of the signature image and that the quantitative evaluation indicators used in this paper can be used for signature authenticity recognition, laying a solid foundation for future signature recognition research.