title: Efficient fuzzy C-means architecture for image segmentation.
abstract: 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.
authors.affiliation: Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei 116, Taiwan. royalfay@gmail.com
authors.forename: Hui-Ya
authors.initials: HY
authors.lastname: Li
authors.forename: Wen-Jyi
authors.initials: WJ
authors.lastname: Hwang
authors.forename: Chia-Yen
authors.initials: CY
authors.lastname: Chang
mesh_terms: D000465:Algorithms; D003199:Computer Systems; D017143:Fuzzy Logic; D007091:Image Processing, Computer-Assisted