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. The selection of the filter banks remains however a crucial issue, as well as determining a relevant combination of these descriptors. To cope with selection and fusion issues, we propose a novel approach relying on the definition of the texture-based similarity measure as a weighted sum of the Kullback

• Type: Journal
• Year: 2008
• Where: PAA
• Authors: Imen Karoui, Ronan Fablet, Jean-Marc Boucher, Wojciech Pieczynski, Jean-Marie Augustin
• Keywords: Distributed And Parallel Computing, Filter Response, PAA 2008, Similarity Measure, Weighting Factors