@inproceedings{59ae433bd2b64dfa86082e3d0dc2f14f,
title = "Content-based image retrieval using hybrid micro-structure descriptor",
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.",
keywords = "CBIR, Descriptor, Image retrieval, Micro-structure",
author = "Ying Li and Pei Zhang",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 ; Conference date: 14-06-2015 Through 16-06-2015",
year = "2015",
doi = "10.1007/978-3-319-23989-7_42",
language = "英语",
isbn = "9783319239873",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "411--419",
editor = "Xiaofei He and Zhi-Hua Zhou and Xinbo Gao and Zhi-Yong Liu and Yanning Zhang and Baochuan Fu and Fuyuan Hu and Zhancheng Zhang",
booktitle = "Intelligence Science and Big Data Engineering",
}