Flower image retrieval method based on ROI feature

An Xiang Hong, Gang Chen, Jun Li Li, Zheru Chi, Dan Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

31 Citations (Scopus)


Flower image retrieval is a very important step for computer-aided plant species recognition. 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 show 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 show 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).
Original languageEnglish
Pages (from-to)764-772
Number of pages9
JournalJournal of Zhejiang University: Science
Issue number7
Publication statusPublished - 1 Jul 2004


  • Color features
  • Flower image characterization
  • Flower image retrieval
  • Knowledge-driven segmentation
  • Region-of-Interest (ROI)
  • Shape features

ASJC Scopus subject areas

  • General Engineering


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