Title :
Measurement of fine particle size with wavelet signature
Author :
Pi, Ming Hong ; Zhang, Hong
Author_Institution :
Dept. of Comput. Sci., Alberta Univ., Edmonton, Alta., Canada
Abstract :
The fine particles of mineral ore are a mixture of granules of various sizes, which collectively look like a texture. It is difficult to estimate the size distribution of such fine particles using conventional image segmentation techniques. In this paper, we propose an image-retrieval-like approach to estimate the size distribution of the fine particles. We introduce a new wavelet signature and a fitting algorithm for wavelet coefficients based on the theory of fragmentation.
Keywords :
computerised instrumentation; image retrieval; particle size measurement; statistical analysis; wavelet transforms; fine particle size measurement; fitting algorithm; image-retrieval-like approach; size distribution; statistical framework; wavelet signature; Data mining; Image databases; Image segmentation; Image texture analysis; Intelligent systems; Particle measurements; Size measurement; Wavelet analysis; Wavelet coefficients; Weibull distribution;
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1530354
