Efficient fuzzy c-means architecture for image segmentation

Hui Ya Li, Wen Jyi Hwang*, Chia Yen Chang

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

11 引文 斯高帕斯(Scopus)

摘要

This paper presents a novel VLSI architecture for image segmentation. The architecture is based on the fuzzy c-means algorithm with spatial constraint for reducing the misclassification rate. In the architecture, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. In addition, an efficient pipelined circuit is used for the updating process for accelerating the computational speed. Experimental results show that the the proposed circuit is an effective alternative for real-time image segmentation with low area cost and low misclassification rate.

原文英語
頁(從 - 到)6697-6718
頁數22
期刊Sensors
11
發行號7
DOIs
出版狀態已發佈 - 2011 七月

ASJC Scopus subject areas

  • 分析化學
  • 生物化學
  • 原子與分子物理與光學
  • 儀器
  • 電氣與電子工程

指紋

深入研究「Efficient fuzzy c-means architecture for image segmentation」主題。共同形成了獨特的指紋。

引用此