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Self-Eigenroughness Selection for Texture Recognition Using Genetic Algorithms

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4678))

  • 1394 Accesses

Abstract

To test the effectiveness of Self-Eigenroughness, which is derived from performing principal component analysis (PCA) on each texture roughness individually, in texture recognition with respect to Eigenroughness, which is derived from performing PCA on all texture roughness; we present a novel fitness function with adaptive threshold to evaluate the performance of each subset of genetically selected eigenvectors. Comparatively studies suggest that the former is superior to the latter in terms of recognition accuracy and computation efficiency.

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References

  1. Fredembach, C., Schröder, M., Süsstrunk, S.: Eigenregions for Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 26, 1645–1649 (2004)

    Article  Google Scholar 

  2. Zhang, J., Tan, T.: Brief Review of Invariant Texture Analysis Methods. Pattern Recognition 35, 735–747 (2002)

    Article  MATH  Google Scholar 

  3. Torres, L., Vilá, J.: Automatic Face Recognition for Video Indexing Applications. Pattern Recognition 35, 615–625 (2002)

    Article  MATH  Google Scholar 

  4. Duda, R.O., Hart, P.E., Stork, D.G. (eds.): Pattern Classification. John Wiley & Sons, Chichester (2000)

    Google Scholar 

  5. Brodatz, P. (ed.): Textures: A Photographic Album for Artists and Designers. Dover, NY (1966)

    Google Scholar 

  6. Vision Texture, http://vismod.media.mit.edu/pub/VisTex/

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Authors and Affiliations

  1. Institute of Photonics and Communications, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, Kaohsiung 807, Taiwan, R.O.C.

    Jing-Wein Wang

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  1. Jing-Wein Wang
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Jacques Blanc-Talon Wilfried Philips Dan Popescu Paul Scheunders

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© 2007 Springer-Verlag Berlin Heidelberg

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Wang, JW. (2007). Self-Eigenroughness Selection for Texture Recognition Using Genetic Algorithms. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_77

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  • DOI: https://doi.org/10.1007/978-3-540-74607-2_77

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74606-5

  • Online ISBN: 978-3-540-74607-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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