Title :
Circular-Mellin features for texture segmentation
Author :
Ravichandran, G. ; Trivedi, Mohan Manubhai
Author_Institution :
Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN
fDate :
12/1/1995 12:00:00 AM
Abstract :
Texture is an important cue in region-based segmentation of images. We provide an insight into the development of a new set of distortion-invariant texture operators. These “circular-Mellin” operators are invariant to both scale and orientation of the target and represent the spectral decomposition of the image scene in the polar-log coordinate system. Coupled with the unique shift invariance property of the correlator architecture, we show that these circular-Mellin operators can be used for rotation-and scale-invariant feature extraction. We note that while these feature extractors have a functional form that is similar to the Gabor operators, they have distortion-invariant characteristics unlike the Gabor functions that make them more suitable for texture segmentation. A detailed analytical description of these operators and segmentation results to highlight their salient properties are presented
Keywords :
correlation methods; feature extraction; functional analysis; image representation; image segmentation; image texture; spectral analysis; Gabor functions; Gabor operators; circular-Mellin features; correlator architecture; distortion invariant characteristics; distortion invariant texture operators; image segmentation; polar-log coordinate system; region based segmentation; rotation invariant feature extraction; scale invariant feature extraction; shift invariance property; spectral decomposition; texture segmentation; Computer vision; Feature extraction; Filtering theory; Higher order statistics; Humans; Image analysis; Image segmentation; Image texture analysis; Layout; Maximum likelihood detection;
Journal_Title :
Image Processing, IEEE Transactions on