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Multi-Object Detection Using Image Segmentation and Salient Points  

Lee, Jeong-Ho (Dept. of Computer Science and Engineering, Hanyang University)
Kim, Ji-Hun (PDP DV R&D Center, LG Electronics Inc.)
Moon, Young-Shik (Dept. of Computer Science and Engineering, Hanyang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.45, no.2, 2008 , pp. 48-55 More about this Journal
Abstract
In this paper we propose a novel method for image retrieval system using image segmentation and salient points. The proposed method consists of four steps. In the first step, images are segmented into several regions by JSEG algorithm. In the second step, for the segmented regions, dominant colors and the corresponding color histogram are constructed. By using dominant colors and color histogram, we identify candidate regions where objects may exist. In the third step, real object regions are detected from candidate regions by SIFT matching. In the final step, we measure the similarity between the query image and DB image by using the color correlogram technique. Color correlogram is computed in the query image and object region of DB image. By experimental results, it has been shown that the proposed method detects multi-object very well and it provides better retrieval performance compared with object-based retrieval systems.
Keywords
Content-based Image Retrieval; Object detection; Feature point;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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