An improved fast FCM image segmentation algorithm based on region feature analysis

作者：Xu Shao Ping^*; Liu Xiao Ping; Li Chun Quan; Hu Ling Yan; Yang Xiao Hui

来源：Pattem Recognition and Aitificial Intelligence, 2012, 25(6): 987-995.

• Cluster validity
• Co-occurrence-matrix
• Fast FCM
• Feature vectors
• Fuzzy C-means algorithms
• Higher efficiency
• Image segmentation algorithm
• Membership matrix
• Noise immunity
• Region feature
• Region segmentation
• Regional characteristics

A fast image segmentation algorithm based on region feature is proposed to estimate centroid number. In the preprocessing analysis stage, the feature vector based on the cooccurrence matrix statistics is used to describe the regional characteristics of sub-image, and the proposed algorithm combines with cluster validity function to estimate accurate centroid number and initialization of membership matrix. In the main clustering stage, the implicit feature of color and texture extracted by Gabor filter is used to accomplish clustering, which not only produces a more reasonable quality of region segmentation, but also has fine noise immunity. The experimental results show that the proposed algorithm effectively overcomes the deficiencies of pixel-level estimations, greatly accelerates the iterative speed of the FCM main clustering stage and achieves higher efficiency in the implementation.

• 出版日期2012