An effective image classification method with the fusion of invariant feature and a new color descriptor

Leila Mansourian; Muhamad Taufik Abdullah; Lili Nurliyana Abdullah; Azreen Azman; Mas Rina Mustaffa

doi:10.1117/12.2266892

8 February 2017 An effective image classification method with the fusion of invariant feature and a new color descriptor

Leila Mansourian, Muhamad Taufik Abdullah, Lili Nurliyana Abdullah, Azreen Azman, Mas Rina Mustaffa

Author Affiliations +

Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 102250Z (2017) https://doi.org/10.1117/12.2266892
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan

Abstract

Pyramid Histogram of Words (PHOW), combined Bag of Visual Words (BoVW) with the spatial pyramid matching (SPM) in order to add location information to extracted features. However, different PHOW extracted from various color spaces, and they did not extract color information individually, that means they discard color information, which is an important characteristic of any image that is motivated by human vision. This article, concatenated PHOW Multi-Scale Dense Scale Invariant Feature Transform (MSDSIFT) histogram and a proposed Color histogram to improve the performance of existing image classification algorithms. Performance evaluation on several datasets proves that the new approach outperforms other existing, state-of-the-art methods.

Citation Download Citation

Leila Mansourian, Muhamad Taufik Abdullah, Lili Nurliyana Abdullah, Azreen Azman, and Mas Rina Mustaffa "An effective image classification method with the fusion of invariant feature and a new color descriptor", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102250Z (8 February 2017); https://doi.org/10.1117/12.2266892

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