Abstract
Along with the speedy increase in the size of digital image collections, the content-based image retrieval (CBIR) has already become one of the hot topics in both image processing and computer vision. And it has been widely used in browsing, searching, and retrieving certain interested information from a huge amount of data. In this paper, we present a hybrid micro-structure descriptor (HMSD) to describe the image feature, which is used for image retrieval. This method makes a color quantization and edge orientation detection of the image in both HSV and RGB color space to extract four kinds of micro-structure and then hybrid these four via an effective way. The experimental results show that the information of images such as color, texture, shape, and color layout can be described more effectively by using this method and the accuracy of image retrieval is improved greatly than several well-known methods.
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Acknowledgments
This work was supported by the Research Fund for the Doctoral Program of Higher Education, China under Grant 20126102110041, the Research Fund for the Key Project of Technology Research Plan of Ministry of Public Security, China under Grant 2014JSYJA018, the Natural Science Research Project of Education Department of Shaanxi Province, China under Grant 12JK0731, and the Royal Academy of Engineering, UK, under Grant 1314RECI025.
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Li, Y., Zhang, P. (2015). Content-Based Image Retrieval Using Hybrid Micro-Structure Descriptor. In: He, X., et al. Intelligence Science and Big Data Engineering. Image and Video Data Engineering. IScIDE 2015. Lecture Notes in Computer Science(), vol 9242. Springer, Cham. https://doi.org/10.1007/978-3-319-23989-7_42
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DOI: https://doi.org/10.1007/978-3-319-23989-7_42
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