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Proceedings Paper

An effective image classification method with the fusion of invariant feature and a new color descriptor
Author(s): Leila Mansourian; Muhamad Taufik Abdullah; Lili Nurliyana Abdullah; Azreen Azman; Mas Rina Mustaffa
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Paper 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.

Paper Details

Date Published: 8 February 2017
PDF: 5 pages
Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102250Z (8 February 2017); doi: 10.1117/12.2266892
Show Author Affiliations
Leila Mansourian, Univ. Putra Malaysia (Malaysia)
Muhamad Taufik Abdullah, Univ. Putra Malaysia (Malaysia)
Lili Nurliyana Abdullah, Univ. Putra Malaysia (Malaysia)
Azreen Azman, Univ. Putra Malaysia (Malaysia)
Mas Rina Mustaffa, Univ. Putra Malaysia (Malaysia)


Published in SPIE Proceedings Vol. 10225:
Eighth International Conference on Graphic and Image Processing (ICGIP 2016)
Yulin Wang; Tuan D. Pham; Vit Vozenilek; David Zhang; Yi Xie, Editor(s)

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