Image Retrieval Using the Intensity Variation Descriptor

被引:16
|
作者
Wei, Zhao [1 ]
Liu, Guang-Hai [1 ]
机构
[1] Guangxi Normal Univ, Coll Comp Sci & Informat Technol, Guilin 541004, Peoples R China
基金
中国国家自然科学基金;
关键词
LOCAL BINARY PATTERNS; UNIFORM DESCRIPTOR; RECEPTIVE FIELDS; COLOR HISTOGRAM; TEXTURE; FEATURES; FRAMEWORK; MANIFOLD;
D O I
10.1155/2020/6283987
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Variations between image pixel characteristics contain a wealth of information. Extraction of such cues can be used to describe image content. In this paper, we propose a novel descriptor, called the intensity variation descriptor (IVD), to represent variations in colour, edges, and intensity and apply it to image retrieval. The highlights of the proposed method are as follows. (1) The IVD combines the advantages of the HSV and RGB colour spaces. (2) It can simulate the lateral inhibition mechanism and orientation-selective mechanism to determine an optimal direction and spatial layout. (3) An extended weighted L1 distance metric is proposed to calculate the similarity of images. It does not require complex operations such as square or square root and leads to good performance. Comparative experiments on two Corel datasets containing 15,000 images show that the proposed method performs better than the SoC-GMM, CPV-THF, and STH methods and provides good matching of texture, colour, and shape.
引用
收藏
页数:12
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