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A flower image retrieval method based on ROI feature.

An-Xiang Hong·Gang Chen·Jun-Li Li·Zhe-Ru Chi·Dan Zhang
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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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AlgorithmsArtificial IntelligenceCluster AnalysisColorColorimetryFlowersImage EnhancementImage Interpretation, Computer-AssistedInformation Storage and RetrievalNumerical Analysis, Computer-AssistedPattern Recognition, AutomatedPhotographyReproducibility of ResultsSensitivity and SpecificitySignal Processing, Computer-AssistedComparative StudyEvaluation StudyJournal ArticleResearch Support, Non-U.S. Gov'tValidation Study

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An-Xiang Hong, Gang Chen, Jun-Li Li, Zhe-Ru Chi, Dan Zhang. 2004. A flower image retrieval method based on ROI feature.. https://doi.org/10.1631/jzus.2004.0764

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