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 language | English |
|---|---|
| Pages (from-to) | 589-592 |
| Number of pages | 4 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Volume | 3 |
| Publication status | Published - 25 Sept 2003 |
| Event | 2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong Duration: 6 Apr 2003 → 10 Apr 2003 |
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering