Title :
Regional objects based image retrieval
Author :
Wu, Jian-Guo ; Wang, Xi-Zhao ; Xing, Hong-Jie
Author_Institution :
Key Lab. of Machine Learning & Comput. Intell., Hebei Univ., Baoding, China
Abstract :
Content-based image retrieval has become an important research area. In order to extract the semantic information within the user´s query concept, we propose an image retrieval method based on regional objects. It is regarded as the pre-processing of a given query image, that is to say, when we get a query image, it needs us to segment the regional object which is useful or interesting, and retrieve according to the segmented fragment. Moreover, we propose a correlation coefficient based color representation. Experimental results demonstrate that our proposed approach performs much better than its related methods. Furthermore, the presented system has a high retrieval precision and keeps color consistency between the similarity images.
Keywords :
content-based retrieval; image colour analysis; image retrieval; image segmentation; color representation; content-based image retrieval; correlation coefficient; image segmentation; query image; regional objects; semantic information extraction; Correlation; Feature extraction; Histograms; Image color analysis; Image retrieval; Image segmentation; Support vector machines; Content-based image retrieval; Correlation coefficient; Pre-processing; Regional objects;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968385