Computer Science ›› 2019, Vol. 46 ›› Issue (7): 258-262.doi: 10.11896/j.issn.1002-137X.2019.07.039

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Image Segmentation Method Based on Improved Pulse Coupled Neural Networks

WANG Yan,XU Xian-fa   

  1. (College of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China)
  • Received:2018-05-07 Online:2019-07-15 Published:2019-07-15

Abstract: In order to implement segmentation of images with multi-object and images with intensity inhomogeneity,this paper proposed an image segmentation method based on region growing with local coupled neural networks (RG-LPCNN).Firstly,the saliency map of the original image is extracted by using saliency detection algorithm.Secondly,the object and the background of the saliency map are coarsely segmented by histogram thresholding method,and centroid of the object is taken as the initial seed point of RG-LPCNN.In addition,convolution results of Gauss kernel and original image are used as amplification coefficients to make the dynamic threshold have local characteristics.Finally,the proposed method is utilized to segment images,implementing the segmentation of the images with multi-object and the images with intensity inhomogeneity.The RG-LPCNN algorithm is compared with other thresholding segmentationalgorithms in natural images and images with intensity inhomogeneity.The results demonstrate that the proposed method has superior segmentation effect for segmentation of the images with multi-object and the images with intensity inhomogeneity.

Key words: Intensity inhomogeneity, Local characteristics, Multi-object, Saliency

CLC Number: 

  • TP183
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