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Directional Discriminant Analysis Based on Nearest Feature Line

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Intelligent Information and Database Systems (ACIIDS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7197))

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Abstract

In this paper, two novel image feature extraction algorithms based on directional filter banks and nearest feature line are proposed, which are named Single Directional Feature Line Discriminant Analysis (SD-NFDA) and Multiple Directional Feature Discriminant Line Analysis (MD-NFDA). SD-NFDA and MD-NFDA extract not only the statistic feature of samples, but also the directionality feature. SD-NFDA and MD-NFDA can get higher average recognition rate with less running time than other nearest feature line based feature extraction algorithms. Experimental results confirm the advantages of SD-NFDA and MD-NFDA.

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Yan, L., Chu, SC., Roddick, J.F., Pan, JS. (2012). Directional Discriminant Analysis Based on Nearest Feature Line. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28490-8_13

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  • DOI: https://doi.org/10.1007/978-3-642-28490-8_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28489-2

  • Online ISBN: 978-3-642-28490-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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