Fuzzy Particle Swarm Optimization Clustering and Its Application to Image Clustering

Image classification and clustering is a challenging problem in computer vision. This paper proposed a kind of particle swarm optimization clustering approach: FPSOC to process image clustering problem. This approach considers each particle as a candidate cluster center. The particles fly in the solution space to search suitable cluster centers. This method is different from previous work in that it employs fuzzy concept in particle swarm optimization clustering and adopts attribute selection mechanism to avoid the ‘curse of dimensionality’ problem. The experimental results show that the presented approach can properly process image clustering problem.

[1]  Martin Szummer,et al.  Indoor-outdoor image classification , 1998, Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database.

[2]  Andries Petrus Engelbrecht,et al.  Particle swarm optimization method for image clustering , 2005, Int. J. Pattern Recognit. Artif. Intell..

[3]  Vapnik,et al.  SVMs for Histogram Based Image Classification , 1999 .

[4]  J. C. Platt.  AutoAlbum: clustering digital photographs using probabilistic model merging , 2000, 2000 Proceedings Workshop on Content-based Access of Image and Video Libraries.

[5]  Mingjing Li,et al.  Semantic image clustering using relevance feedback , 2003, Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03..

[6]  Jiebo Luo,et al.  Bayesian fusion of camera metadata cues in semantic scene classification , 2004, CVPR 2004.

[7]  Patrick Haffner,et al.  Support vector machines for histogram-based image classification , 1999, IEEE Trans. Neural Networks.

[8]  Aidong Zhang,et al.  SemQuery: Semantic Clustering and Querying on Heterogeneous Features for Visual Data , 2002, IEEE Trans. Knowl. Data Eng..

[9]  R. Eberhart,et al.  Fuzzy adaptive particle swarm optimization , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[10]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[11]  Morshed U. Chowdhury,et al.  Image semantic classification by using SVM , 2003 .

[12]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[13]  Andries Petrus Engelbrecht,et al.  Data clustering using particle swarm optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[14]  Gao Wen,et al.  Exploiting multi-context Analysis in Semantic Image Classification , 2005 .

[15]  Andries Petrus Engelbrecht,et al.  A Color Image Quantization Algorithm Based on Particle Swarm Optimization , 2005, Informatica.

[16]  Xin Yao,et al.  Evolving artificial neural networks , 1999, Proc. IEEE.