Multi-module Image Classification System

In this paper, we propose an image classification system employing multiple modules. The proposed system hierarchically categorizes given sports images into one of the predefined sports classes, eight in this experiment. The image first categorized into one of the two classes in the global module. The corresponding local module is selected accordingly, and then used in the local classification step. By employing multiple modules, the system can specialize each local module properly for the given class feature. The simulation results show that the proposed system successfully classifies images with the correct rate of over 70%.

[1]  Anil K. Jain,et al.  On image classification: city images vs. landscapes , 1998, Pattern Recognit..

[2]  Kiyohiro Shikano,et al.  Modularity and scaling in large phonemic neural networks , 1989, IEEE Trans. Acoust. Speech Signal Process..

[3]  C. A. Kamm,et al.  Improving a phoneme classification neural network through problem decomposition , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

[4]  Ramin Zabih,et al.  Histogram refinement for content-based image retrieval , 1996, Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96.

[5]  Michael I. Jordan,et al.  Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks , 1990, Cogn. Sci..

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

[7]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[8]  Daniel N. Osherson,et al.  Modular learning , 1993 .

[9]  Rosalind W. Picard,et al.  Texture orientation for sorting photos "at a glance" , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[10]  T. Kanade,et al.  Color information for region segmentation , 1980 .

[11]  Michael I. Jordan,et al.  Hierarchical Mixtures of Experts and the EM Algorithm , 1994, Neural Computation.

[12]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  F. J. Śmieja,et al.  Multiple Network Systems (Minos) Modules: Task Division and Module Discrimination , 1991 .