An Effective Image Classification Method with the Fusion of Invariant Feature and a New Color Descriptor

被引:0
|
作者
Mansourian, Leila [1 ]
Abdullah, Muhamad Taufik [1 ]
Abdullah, Lili Nurliyana [1 ]
Azman, Azreen [1 ]
Mustaffa, Mas Rina [1 ]
机构
[1] Univ Putra Malaysia, Fac Comp Sci & Informat Technol, Dept Multimedia, Upm Serdang, 43400, Malaysia
关键词
Saliency map; PHOW MSDSIFT feature; Bag of Visual Words model (BoVW); Dominant Color Description (DCD); image retrieval; Pyramidal Histogram of Visual Words (PHOW);
D O I
10.1117/12.2266892
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
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.
引用
收藏
页数:5
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