DocumentCode
2030432
Title
Structural Texture Segmentation using Affine Symmetry
Author
Park, Heechan ; Martin, Graham R. ; Bhalerao, Abhir H.
Author_Institution
Univ. of Warwick, Coventry
Volume
2
fYear
2007
fDate
Sept. 16 2007-Oct. 19 2007
Abstract
Many natural textures comprise structural patterns and show strong self-similarity. We use affine symmetry to segment an image into self-similar regions; that is a patch of texture (blocks from a uniformly partitioned image) can be transformed to other similar patches by warping. If the texture image contains multiple regions, we then cluster patches into a number of classes such that the overall warping error is minimized. Discovering the optimal clusters is not trivial and known methods are computationally intensive due to the affine transformation. We demonstrate efficient segmentation of structural textures without affine computation. The algorithm uses Fourier Slice Analysis to obtain a spectral contour signature. Experimental evaluation on structural textures shows encouraging results and application on natural images demonstrates identification of texture objects.
Keywords
Fourier analysis; affine transforms; image segmentation; image texture; natural scenes; object recognition; Fourier slice analysis; affine symmetry; affine transformation; image segmentation; image warping; natural images; object identification; optimal clusters; self-similar regions; spectral contour signature; structural patterns; structural texture segmentation; uniformly partitioned image; warping error; Algorithm design and analysis; Clustering algorithms; Computer science; Data mining; Feature extraction; Fourier transforms; Image processing; Image segmentation; Independent component analysis; Surveillance;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location
San Antonio, TX
ISSN
1522-4880
Print_ISBN
978-1-4244-1437-6
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2007.4379089
Filename
4379089
Link To Document