Title :
Gaussian mixture models of texture and colour for image database retrieval
Author :
Permuter, H. ; Francos, J. ; Jermyn, I.H.
Author_Institution :
Dept. of Electr. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
Abstract :
We introduce Gaussian mixture models of ´structure´ and colour features in order to classify coloured textures in images, with a view to the retrieval of textured colour images from databases. Classifications are performed separately using structure and colour and then combined using a confidence criterion. We apply the models to the VisTex database and to the classification of man-made and natural areas in aerial images. We compare these models with others in the literature, and show an overall improvement in performance.
Keywords :
Gaussian distribution; content-based retrieval; feature extraction; image classification; image colour analysis; image retrieval; image texture; remote sensing; visual databases; Gaussian mixture models; VisTex database; aerial images; coloured texture classification; confidence criterion; image database retrieval; man-made areas; natural areas; performance; structure features; textured colour images; Color; Data engineering; Hidden Markov models; Image databases; Image processing; Image retrieval; Information retrieval; Layout; Spatial databases; Wavelet coefficients;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
Print_ISBN :
0-7803-7663-3
DOI :
10.1109/ICASSP.2003.1199538