Image Recognition Based on Kernel Self-optimized Learning

Shou-Po Bu, Shu-Chuan Chu, Xun-Fei Liu, John Roddick

    Research output: Contribution to conferencePaperpeer-review

    1 Citation (Scopus)

    Abstract

    Image recognition technologies have been used in many areas, and feature extraction of image is key step for image recognition. A novel feature extraction method using kernel self-optimized learning for image recognition. The scheme of image feature extraction includes textural extraction using Gabor wavelet, textural features reduction based on class-wise locality preserving projection with the nearest neighbor graph and common kernel discriminant vector. The nearest neighbor classifier is applied to image classification. The feasibility and performance of the algorithm are testified in the public image databases.

    Original languageEnglish
    Pages73-76
    Number of pages4
    DOIs
    Publication statusPublished - 1 Dec 2011
    Event2nd International Conference on Innovations in Bio-inspired Computing and Applications -
    Duration: 16 Dec 2011 → …

    Conference

    Conference2nd International Conference on Innovations in Bio-inspired Computing and Applications
    Period16/12/11 → …

    Keywords

    • fractional power polynomial models
    • locality

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