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A Feature Encoding Based on Low Space Complexity Codebook Called Fuzzy Codebook for Image Recognition

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Abstract

For image recognition, a codebook approach is generally used for representing an image to a feature vector. In this approach, the codebook, which is visual vocabulary, is generated for each local feature framework in the case of using multiple local feature frameworks. Hence, the codebook is required that is a small memory footprint. Image representation based on a compact codebook by using fuzzy clustering has been presented, but it includes a high computational complexity operation. This paper presents a reducing computational complexity in the image representation step and experimental results of online classifier.

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Number 25330240.

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Authors and Affiliations

  1. Graduate School of System Engineering, Kochi University of Technology, Kami, Japan

    Yuki Shinomiya

  2. School of System engineering, Kochi University of Technology, Kami, Japan

    Yukinobu Hoshino

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  1. Yuki Shinomiya
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  2. Yukinobu Hoshino
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Correspondence to Yukinobu Hoshino.

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Shinomiya, Y., Hoshino, Y. A Feature Encoding Based on Low Space Complexity Codebook Called Fuzzy Codebook for Image Recognition. Int. J. Fuzzy Syst. 21, 274–280 (2019). https://doi.org/10.1007/s40815-018-0568-2

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  • DOI: https://doi.org/10.1007/s40815-018-0568-2

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