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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/27920

Title: Adaptive image segmentation for region-based object retrieval using generalized Hough transform
Authors: Chi-Han Chung;Shyi-Chyi Cheng;Chin-Chun Chang
Contributors: NTOU:Department of Computer Science and Engineering
國立臺灣海洋大學:資訊工程學系
Keywords: Object recognition;Hough transform;Image segmentation;Information retrieval
Date: 2010-10
Issue Date: 2011-10-21T02:34:29Z
Publisher: Pattern Recognition
Abstract: Abstract:Finding an object inside a target image by querying multimedia data is desirable, but remains a challenge. The effectiveness of region-based representation for content-based image retrieval is extensively studied in the literature. One common weakness of region-based approaches is that perform detection using low level visual features within the region and the homogeneous image regions have little correspondence to the semantic objects. Thus, the retrieval results are often far from satisfactory. In addition, the performance is significantly affected by consistency in the segmented regions of the target object from the query and database images. Instead of solving these problems independently, this paper proposes region-based object retrieval using the generalized Hough transform (GHT) and adaptive image segmentation. The proposed approach has two phases. First, a learning phase identifies and stores stable parameters for segmenting each database image. In the retrieval phase, the adaptive image segmentation process is also performed to segment a query image into regions for retrieving visual objects inside database images through the GHT with a modified voting scheme to locate the target visual object under a certain affine transformation. The learned parameters make the segmentation results of query and database images more stable and consistent. Computer simulation results show that the proposed method gives good performance in terms of retrieval accuracy, robustness, and execution speed.
Relation: 43(10), pp. 3219-3232
URI: http://ntour.ntou.edu.tw/handle/987654321/27920
Appears in Collections:[資訊工程學系] 期刊論文

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