Title :
Object classification using mixed color feature
Author :
Gao, Y.Y. ; Zhang, Y.J.
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
Abstract :
This paper proposes a color feature called mixed color feature (MCF) to describe the image contents in terms of human visual perception. Construction and distance measurement of MCF is interpreted in detail. A nonlinear quantizer is proposed to improve the efficiency of MCF. To evaluate the effect and accuracy of MCF in practice, a practical implementation of MCF in object classification is carried out. First, the major histogram (MH) is extracted from MCF as the basic feature in the classification processing; second, weighted nearest matching (WNM) is presented and applied to accomplish the classification. A comparison experiment is carried out and the results show the advantage and efficiency of the proposed method
Keywords :
image classification; image colour analysis; image matching; visual databases; distance measurement; human visual perception; image contents; major histogram; mixed color feature; nonlinear quantizer; object classification; weighted nearest matching; Color; Displays; Feature extraction; Histograms; Humans; Image representation; Image retrieval; Indexing; Printing; Visual perception;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
0-7803-6293-4
DOI :
10.1109/ICASSP.2000.859225