关键词：焊接缺陷检测；图像分割;指数交叉熵;脉冲耦合神经网络；电子信息
摘 要：Aiming at welding defect image with complex background and low contrast,a segmentation method of welding defect image based on exponential cross entropy and improved pulse coupled neural network (PCNN) is proposed.Firstly,the area of weld is extracted by gray projection algorithm.Then,link weighted matrix and dynamic threshold function of PCNN are improved.Finally,the exponential cross entropy is calculated as criterion to determine the number of iteration for improved PCNN and get the optimal segmented image.The experimental results are given.Compared with the threshold segmentation method based on exponential cross entropy,the segmentation method based on PCNN and Shannon entropy,the proposed method can achieve better segmented results.