| A flower image retrieval method based on ROI feature |
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| 作者姓名： | 洪安祥 陈刚 李均利 池哲儒 张亶 |
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| 作者单位： | Department of Applied Mathematics，Department of Applied Mathematics，Department of Applied Mathematics，Center for Multimedia Signal Processing，Department of Electronic and Information Engineering，Hong Kong Polytechnic University，Hong Kong，China，Computer Science College，Zhejiang University，Hangzhou 310027，China |
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| 基金项目： | Project (Nos. 60302012，60202002) supported by the Nationa
Natural Science Foundation of China and the Research Grant
Council of the Hong Kong Special Administrative Region (No
PolyU 5119.01E)，China |
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| 摘 要： | INTRODUCTION There are about 250000 named species offlowering plants and many plant species that havenot been classified and named. Plant classificationand identification is a very old field. So far, thistime-consuming process has mainly been carriedout by taxonomists and/or botanists. A significantimprovement can be expected if the plant identifi-cation can be carried out by a computer automati-cally or semi-automatically with the aid of imageprocessing and computer vision techniqu…
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A flower image retrieval method based on ROI feature |
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| HONG An-xiang,CHEN Gang,LI Jun-li CHI Zhe-ru ZHANG Dan.A flower image retrieval method based on ROI feature[J].Journal of Zhejiang University Science,2004(7). |
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| Authors: | HONG An-xiang CHEN Gang LI Jun-li CHI Zhe-ru ZHANG Dan |
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| Abstract: | Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999). |
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| Keywords: | Flower image retrieval Knowledge-driven segmentation Flower image characterization Region-of-Interest (ROI) Color features Shape features |
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