Title :
Segmenting modulated line textures with S-Gabor filters
Author :
Hickinbotham, Simon J. ; Hancock, Edwin R. ; Austin, James
Author_Institution :
Dept. of Comput. Sci., York Univ., UK
Abstract :
This paper describes a novel technique for segmenting frequency modulated line-textures. Textures of this sort abound in nature and are typified by growth patterns in which the deposition rate varies over time. The basic idea underpinning the technique is to use the S-Gabor kernel as a frequency modulated channel response function. According to this channel model, the central frequency changes exponentially with distance from the centre of the kernel. In order to segment the resulting texture response, we use fuzzy clustering to locate peaks in the Fourier power spectrum. In this way we estimate both the centre-frequency and the modulation parameters of the filter bank. We illustrate the effectiveness of our technique on the segmentation of growth patterns on fish scales
Keywords :
aquaculture; band-pass filters; biology computing; edge detection; filtering theory; frequency estimation; frequency modulation; fuzzy systems; image segmentation; spectral analysis; Fourier power spectrum; S-Gabor filters; S-Gabor kernel; central frequency; centre frequency estimation; channel model; deposition rate; filter bank; fish scales; frequency modulated channel response function; frequency modulated line textures; fuzzy clustering; growth patterns; image texture; modulated line texture segmentation; modulation parameter estimation; texture response; Computer science; Computer vision; Filter bank; Frequency modulation; Gabor filters; Image edge detection; Image segmentation; Kernel; Marine animals; Phase detection;
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
DOI :
10.1109/ICIP.1996.560405