To segment the infrared insulator image efficiently, an improved Unit-linking PCNN algorithm, which makes improvements on both the linking coefficient b and the standard for choosing the best segmented image, is proposed in this paper. The relationship of the gray value of each neuron is used to determine the linking coefficient b and MSE, which consider the relationship between the gray value of the original image and the segmented image, is used to determine the best segmented image. The proposed algorithm is tested on both the standard test images and the aerial infrared images and the results show that the proposed algorithm gives better segmentation of the target image and better vision effect and less time are needed to get the best one.
Digital Object Identifier (DOI)
Cui, Kebin; Li, Baoshu; Yuan, Jinsha; and Wang, Ping
"An Improved Unit-Linking PCNN for Segmentation of Infrared Insulator Image,"
Applied Mathematics & Information Sciences: Vol. 08:
6, Article 38.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss6/38