基于纹理特征的SUSAN图像边缘检测OA

To adapt to cherry images with different morphological characteristics and effectively capture the edges of cherry images,in this paper,a modified SUSAN edge detection algorithm combining texture information is proposed,leveraging the characteristic that texture information is more universal than grayscale information.Firstly,after binarizing the image,the texture features are extracted.Next,the SUSAN operator is applied to traverse the feature map to detect and extract the object edges.Finally,comparative analysis is conducted through simulation experiments to evaluate the performance of the algorithm before and after improvement.The results show that the improved edge detection method effectively captures the edges of the cherry images while preserving fine details,demonstrating strong robustness.The proposed algorithm outperforms other methods in terms of detection performance.