Title :
Texture segmentation using multiscale Hurst features
Author :
Kaplan, Lance M. ; Murenzi, Romain
Author_Institution :
Dept. of Eng., Clark Atlanta Univ., GA, USA
Abstract :
We evaluate the effectiveness of multiscale Hurst parameters as features for texture segmentation. These extended Hurst features quantize texture roughness at various scales. The performance of these new features are compared against standard Hurst features using images of texture mosaics. For the experiments, the performance was evaluated with and without supplemental contrast and average grayscale features
Keywords :
feature extraction; image segmentation; image texture; parameter estimation; quantisation (signal); average grayscale features; contrast; experiments; extended Hurst features; extended self-similarity; image texture; multiscale Hurst features; multiscale Hurst parameters; performance evaluation; standard Hurst features; texture mosaics; texture roughness quantization; texture segmentation; Digital images; Electronic switching systems; Fractals; Humans; Image motion analysis; Image segmentation; Image texture analysis; Layout; Remote monitoring; Shape;
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
DOI :
10.1109/ICIP.1997.632056
