Publication: A new feature extractor invariant to intensity, rotation, and scaling of color images
Issued Date
2006-07-22
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ISSN
00200255
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2-s2.0-33646163435
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Mahidol University
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SCOPUS
Bibliographic Citation
Information Sciences. Vol.176, No.14 (2006), 2097-2119
Suggested Citation
Kingkarn Sookhanaphibarn, Chidchanok Lursinsap A new feature extractor invariant to intensity, rotation, and scaling of color images. Information Sciences. Vol.176, No.14 (2006), 2097-2119. doi:10.1016/j.ins.2005.10.005 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/23200
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Title
A new feature extractor invariant to intensity, rotation, and scaling of color images
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Abstract
This paper proposes a new method for extracting the invariant features of an image based on the concept of principal component analysis and a competitive learning algorithm. The proposed algorithm can be applied to binary, gray-level, or colored-texture images with a size greater than 256 × 256 pixels. In addition to translation, scaling, and rotation invariant extraction, the extraction of a feature invariant to color intensity can be implemented by using this method. In our experiment, the proposed method shows the capability to differentiate images having the same shape but different colored textures. The experimental results report the effectiveness of this technique and its performance as measured by recognition accuracy rate and computational time. These results are also compared with those obtained by classical techniques. © 2005 Elsevier Inc. All rights reserved.