Color image segmentation based on wavelet transformation and SOFM neural network

Zhang Jun, Zhang Qieshi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Image segmentation, which is the first essential and fundamental issue in the image analysis and pattern recognition, is a classical difficult problem in the image processing. The color images, which possess more visual information than the gray images do, have aroused more and more attentions. In the medical imaging system, according to the different absorbency of different tissues, the staining method is often used to get the color image which provides more abundant information for diagnosis. As for the automatic analysis system of kidney-tissue image stained by Periodic Acid Schiff (PAS), the correct segmentation of glomerulus is an important step. A layer-color clustering segmentation method based on wavelet transformation and self-organizing feature map neural network (SOFM) is proposed in this paper. Firstly, the wavelet transformation is applied to the original images to get the low frequency images to improve the running efficiency. Secondly, the disordered method based on random number is performed to improve the performance of SOFM. Thirdly, the layer-color clustering using SOFM is executed until the final error can meet the need of the average color error (ACE) and then the clustered image and the palette can be acquired. Finally, based on the histogram of palette, the glomerulus can be segmented from the kidney-tissue image correctly. Experimental results show the good performance of this method.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Robotics and Biomimetics, ROBIO
Pages1778-1781
Number of pages4
DOIs
Publication statusPublished - 2008
Event2007 IEEE International Conference on Robotics and Biomimetics, ROBIO - Yalong Bay, Sanya
Duration: 2007 Dec 152007 Dec 18

Other

Other2007 IEEE International Conference on Robotics and Biomimetics, ROBIO
CityYalong Bay, Sanya
Period07/12/1507/12/18

Fingerprint

Self organizing maps
Image segmentation
Color
Neural networks
Tissue
Periodic Acid
Medical imaging
Imaging systems
Image analysis
Pattern recognition
Image processing
Acids

Keywords

  • Average color error
  • Layer-color clustering
  • SOFM neural network
  • Wavelet transformation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering
  • Biomaterials

Cite this

Jun, Z., & Qieshi, Z. (2008). Color image segmentation based on wavelet transformation and SOFM neural network. In 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO (pp. 1778-1781). [4522435] https://doi.org/10.1109/ROBIO.2007.4522435

Color image segmentation based on wavelet transformation and SOFM neural network. / Jun, Zhang; Qieshi, Zhang.

2007 IEEE International Conference on Robotics and Biomimetics, ROBIO. 2008. p. 1778-1781 4522435.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jun, Z & Qieshi, Z 2008, Color image segmentation based on wavelet transformation and SOFM neural network. in 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO., 4522435, pp. 1778-1781, 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO, Yalong Bay, Sanya, 07/12/15. https://doi.org/10.1109/ROBIO.2007.4522435
Jun Z, Qieshi Z. Color image segmentation based on wavelet transformation and SOFM neural network. In 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO. 2008. p. 1778-1781. 4522435 https://doi.org/10.1109/ROBIO.2007.4522435
Jun, Zhang ; Qieshi, Zhang. / Color image segmentation based on wavelet transformation and SOFM neural network. 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO. 2008. pp. 1778-1781
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