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» Texture classification using invariant ranklet features
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CVPR
2005
IEEE
15 years 11 months ago
Efficient Image Matching with Distributions of Local Invariant Features
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
Kristen Grauman, Trevor Darrell
ISBI
2006
IEEE
15 years 10 months ago
Texture-based segmentation of the knee bones in MRI using phase information
This paper considers the problem of tissue classification in 3D MRI by the mean of texture analysis. The main contribution is the use of the phase of the complex MR image, to deri...
Peter Stanwell, Pierrick Bourgeat, Sébastie...
ICIP
2006
IEEE
15 years 11 months ago
Texture Classification with Ants
In this paper, we present a novel texture classification algorithm inspired by the self-assembling behavior of real ants when building live structures with their bodies. The propo...
Arshad Hussain, Nasir Rajpoot, Kashif Rajpoot
PR
2006
77views more  PR 2006»
14 years 9 months ago
Preserving boundaries for image texture segmentation using grey level co-occurring probabilities
Texture analysis has been used extensively in the computer-assisted interpretation of digital imagery. A popular texture feature extraction approach is the grey level co-occurrenc...
Rishi Jobanputra, David A. Clausi
PAA
2008
14 years 9 months ago
Fusion of textural statistics using a similarity measure: application to texture recognition and segmentation
Abstract Features computed as statistics (e.g. histograms) of local filter responses have been reported as the most powerful descriptors for texture classification and segmentation...
Imen Karoui, Ronan Fablet, Jean-Marc Boucher, Wojc...