Title :
An improved EM algorithm for content based image retrieval
Author :
Yu, Mingyan ; Liu, Haiyuan ; Qiu, Yanhang ; Yan, Ying
Author_Institution :
Inf. Technol. Dept., Guangdong Commun. Polytech., Guangzhou, China
Abstract :
Content Based Image Retrieval (CBIR) mainly contains two phases: first, to represent an image; second, to measure the dissimilarity between two images. Expectation-Maximization (EM) is a popular algorithm for clustering Gauss mixtures for the image representation, but the greedy nature of EM make it hard to get an optimal model for CBIR. In this paper , we introduce an improved EM algorithm for clustering Gaussian Mixtures (GMs) to represent an image, instead of regular EM algorithm. We also use different dissimilarity measures for different queries according to their statistics features. Experiments show this approach can greatly improve the performance of CBIR.
Keywords :
Gaussian processes; content-based retrieval; expectation-maximisation algorithm; image representation; image retrieval; pattern clustering; EM algorithm; Gauss mixture clustering; content based image retrieval; expectation-maximization algorithm; image dissimilarity measurement; image representation; statistics features; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Image color analysis; Image retrieval; CBIR; EM; EMD; GM;
Conference_Titel :
Computer Science and Service System (CSSS), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9762-1
DOI :
10.1109/CSSS.2011.5974516
