Image Retrieval Using the Intensity Variation Descriptor
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-09
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Wei, Zhao& Liu, Guang-Hai. 2020. Image Retrieval Using the Intensity Variation Descriptor. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1196655
Modern Language Association (MLA)
Wei, Zhao& Liu, Guang-Hai. Image Retrieval Using the Intensity Variation Descriptor. Mathematical Problems in Engineering No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1196655
American Medical Association (AMA)
Wei, Zhao& Liu, Guang-Hai. Image Retrieval Using the Intensity Variation Descriptor. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1196655
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196655