Computer texture boundary detection based on human visual perception model

Texture boundaries detection is considered a difficult problem. In human visual perception, however, discriminating textures is an "effortless" process. Based on the human pre-attentive texture perception model called texton, we propose a set of computational algorithms to extract textural features and form the texton energy map. We then use a neural positive feedback algorithm for boundary extraction. The model and algorithms are tested on simulated and real-life pictures and are found to yield very satisfactory results.<<ETX>>

[1]  B. Julesz,et al.  Human factors and behavioral science: Textons, the fundamental elements in preattentive vision and perception of textures , 1983, The Bell System Technical Journal.

[2]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Dennis Gabor,et al.  Theory of communication , 1946 .

[4]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[5]  J.G. Daugman,et al.  Entropy reduction and decorrelation in visual coding by oriented neural receptive fields , 1989, IEEE Transactions on Biomedical Engineering.