Region-of-interest based flower images retrieval

A. Hong, Zheru Chi, G. Chen, Z. Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Flower image retrieval is a very important step for computer-aided plant species identification. 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 a flower and two shape-based sets of features, 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 approach based on color clustering and domain knowledge can achieve accurate flower regions. The retrieval results on a database of 885 flower images collected from 14 plant species show that our region-of-interest (ROI) based retrieval approach can perform better than the Swain method based on the global color histogram (Swain, M.J. and Ballard, D.H., Int. J. of Computer Vision, vol.7, no.1, p.11-32, 1991).
Original languageEnglish
Title of host publication2003 IEEE International Conference on Acoustics, Speech, and Signal Processing : proceedings : April 6-10, 2003, Hong Kong Exhibition and Convention Centre, Hong Kong
Number of pages1
ISBN (Print)0780376633
Publication statusPublished - 2003

Publication series

NameIEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN (Print)1520-6149


  • Botany
  • Feature extraction
  • Image colour analysis
  • Image retrieval
  • Image segmentation
  • Pattern clustering


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