Application of hierarchical self-organizing mapping to invariant recognition of color-texture images
Sookhanaphibarn, K., Wong, K.W. and Lursinsap, C. (2002) Application of hierarchical self-organizing mapping to invariant recognition of color-texture images. In: 9th International Conference on Neural Information Processing (ICONIP '02), 18-22 November 2002, Singapore pp. 2113-2117.
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In this paper, we present a hierarchical self-organizing map applying to scaling and rotation invariant recognition of a 256×256-pixel color-texture image. Since Kohonen's self-organizing mapping is not embedded with the invariant ability, some learning modifications are added in rotation and scaling invariant self-organizing map (RSISOM). The concept of hierarchy self-organizing map, furthermore, is developed to improve the performance of RSISOM for a color image recognition. In the experiment, the proposed algorithm shows the efficient invariant capability under scaling and rotation as well as the distinguish capability in different color-texture images. Furthermore, the computational time after applying the concept of Hierarchy in RSISOM approach is three times less than the computational time of the original RSISOM.
|Publication Type:||Conference Paper|
|Murdoch Affiliation:||School of Information Technology|
|Copyright:||© 2002 IEEE|
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