ROISeer: Region-Based Image Retrieval by Hierarchical Feature Filtering

Authors:
Zou Lei;Bizhong Wei;Xiaodong Cai;Yuelin Chen
Affiliations:
School of Applied Science and Technology, Guilin University of Electronic Technology, China;School of Applied Science and Technology, Guilin University of Electronic Technology, China;School of Applied Science and Technology, Guilin University of Electronic Technology, China;School of Applied Science and Technology, Guilin University of Electronic Technology, China
Venue:
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Year:
2008

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Abstract

In this paper, an image retrieval system, ROISeer is proposed. ROISeer uses a region-based approach for feature extraction, and integrated region matching based upon color and shape similarity measurements. Different from most existing image query by example systems, the proposed system provides a hierarchical feature filtering instead of using single or multiple features fusion. It considers that color feature is the most significant factor simulating the attention of Human Visual System (HVS), therefore image segmentation procedure is only applied for those image where similar color patch is presented. The novel design of this technique significantly reduces the complexity of image segmentation for large scale image databases. In addition, to enhance the reliability of the system, a region-based shape matching algorithm is utilized. This method ensures that the same region is robustly retrieved when the target is rotated, resized and shifted. Experimental results show that the ROISeer provides robust and well performance in Region of Interest (ROI) retrieval in single category or cross-category image databases.