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2009 WRI World Congress on Computer Science and Information Engineering
Object Feature Extraction for Image Retrieval Based on Quadtree Segmented Blocks
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
This study proposed a new object feature extraction method that employs the quadtree decomposition. In the proposed method, we segmented the image into variable sized blocks, named homogeneous blocks, which are the units of feature extraction process. Because the quadtree decomposition can highlight the details of images, more feature information can be extracted from the visual important objects than from the monotone areas of the image. The experimental results show the image retrieval performance is effectively improved as compared with the pixel based method.
Index Terms:
vector quantization, content-based image retrieval, feature extracting, quadtree decomposition
Citation:
Shou-Yi Tseng, Zhi-Yu Yang, Wen-Hsuan Huang, Chin-Yi Liu, Yi-Huei Lin, "Object Feature Extraction for Image Retrieval Based on Quadtree Segmented Blocks," csie, vol. 6, pp.401-405, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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