Region-of-interest based flower images retrieval

Anxiang Hong, Zheru Chi, Gang Chen, Zhiyong Wang

Research output: Journal article publicationConference articleAcademic researchpeer-review

12 Citations (Scopus)

Abstract

Flower image retrieval is a very important step for computer-aided plant species identification. 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 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's method based on global color histogram.
Original languageEnglish
Pages (from-to)589-592
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
Publication statusPublished - 25 Sep 2003
Event2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong
Duration: 6 Apr 200310 Apr 2003

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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