Edge Detection Combined Entropy Threshold and Self-Organizing Map (SOM)

  • Kun Wang
  • Liqun Gao
  • Zhaoyu Pian
  • Li Guo
  • Jianhua Wu
Conference paper

DOI: 10.1007/978-3-540-72393-6_111

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4492)
Cite this paper as:
Wang K., Gao L., Pian Z., Guo L., Wu J. (2007) Edge Detection Combined Entropy Threshold and Self-Organizing Map (SOM). In: Liu D., Fei S., Hou Z., Zhang H., Sun C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg

Abstract

An edge detection method by combining image entropy and Self -Organizing Map (SOM) is proposed in this paper. First, according to information theory image entropy is used to curve up the smooth region and the region of gray level abruptly changed. Then we transform the gray level image to ideal binary pattern of pixels. We define six classes’ edge and six edge prototype vectors. These edge prototype vectors are fed into input layer of the Self-Organizing Map (SOM). Classifying the type of edge through this network, the edge image is obtained. At last, the speckle edges are discarded from the edge image. Experimental results show that it gained better edge image compared with Canny edge detection method.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Kun Wang
    • 1
  • Liqun Gao
    • 1
  • Zhaoyu Pian
    • 1
  • Li Guo
    • 1
  • Jianhua Wu
    • 1
  1. 1.College of Information Science & Engineering, Northeastern University, P.O. Box 135, 110004, ShenyangChina

Personalised recommendations