Local Texton Dissimilarity with applications on biomass classification
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This paper aims to present a novel texture dissimilarity measure based on textons, namely the Local Texton Dissimilarity (LTD), inspired from (Dinu et al., 2012) ...
Abstract: Texture classification, texture synthesis, or similar tasks are an active topic in computer vision and pattern recognition.
Abstract: Texture classification, texture synthesis, or similar tasks are an active topic in computer vision and pattern recognition.
Local texton dissimilarity with applications on biomass classification. January 2014. Authors: Radu Tudor Ionescu at University of Bucharest · Radu Tudor ...
This paper aims to present a novel texture dissimilarity measure based on textons, namely the Local Texton Dissimilarity (LTD), inspired from (Dinu et al., 2012) ...
... {Local Texton Dissimilarity with Applications on Biomass Classification}", year = {2014}, journal = {Proceedings of VISAPP}, month = {January}, address ...
The second system is based on a novel dissimilarity for texture images, namely Local Texton Dissimilarity (LTD), initially introduced by Ionescu et al.
Local Texton Dissimilarity aims at classifying texture images. It is based on textons , which are represented as a set of features extracted from image patches ...
May 8, 2024 · Local Texton Dissimilarity with Applications on Biomass Classification. VISAPP (1) 2014: 593-600; 2013. [c1]. view. electronic edition via DOI ...
The Biomass Texture data set 2.0 contains 360 images of 512x512 pixels representing close up photos of four types of biomass resulted after the processing.