Title :
Segmentation-Based Image Retrieval
Author :
Zhang, Zhen-hua ; Lu, Yi-Nan ; Li, Wen-Hui ; Wang, Gang
Author_Institution :
Jilin Univ., Changchun
Abstract :
Color features are important to pictures and they are easy to calculate. Therefore, the features are widely used in content-based image retrieval (CBIR)[4][7]. In the meantime, it lacks space information. In this paper, color spaces are analyzed and YUV color space is chosen. Color and texture features are extracted in segmentation block, so there are space information. Major color, major segmentation block, a new kind of color quantization and a new Gray scale co-existing matrix´s method are proposed. Our approach is described in detail and compared with other methods presented in the literature to deal with the same problem. The experiments are finished and show that the method in this paper is effective and efficient.
Keywords :
image colour analysis; image retrieval; image segmentation; image texture; matrix algebra; color features; gray scale co-existing matrix; segmentation-based image retrieval; texture features; Content based retrieval; Cybernetics; Data mining; Feature extraction; Humans; Image color analysis; Image retrieval; Image segmentation; Machine learning; Programming profession; Color histogram; Content-based image retrieval (CBIR); Image retrieval; Image segmentation; Texture feature;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370428