Abstract

A new welding seam image segmentation method based on pulse-coupled neural network (PCNN) is presented in this paper. The method segments image by utilizing PCNN’s specific feature that the fire of one neuron can capture firing of its adjacent neurons due to their spatial proximity and intensity similarity. The method can automatically confirm the best iteration times by comparing the maximum of variance ratio and get the best segmentation results. Experimental results show that the proposed method has good performance in both results and execution efficiency.

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