The Experts below are selected from a list of 122520 Experts worldwide ranked by ideXlab platform
Odemir Martinez Bruno - One of the best experts on this subject based on the ideXlab platform.
-
color Texture Analysis based on fractal descriptors
Pattern Recognition, 2012Co-Authors: André Ricardo Backes, Dalcimar Casanova, Odemir Martinez BrunoAbstract:Color Texture classification is an important step in image segmentation and recognition. The color information is especially important in Textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color Texture Analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a Texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color Texture Analysis methods.
-
Texture Analysis based on maximum contrast walker
Pattern Recognition Letters, 2010Co-Authors: André Ricardo Backes, Alexandre Souto Martinez, Odemir Martinez BrunoAbstract:Recently, the deterministic tourist walk has emerged as a novel approach for Texture Analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional Texture Analysis methods in the classification of a set of Brodatz Textures and their rotated versions, thus confirming the potential of the method as a feasible Texture Analysis methodology.
Eglin Véronique - One of the best experts on this subject based on the ideXlab platform.
-
Arabic font recognition based on a Texture Analysis
2014 14th International Conference on Frontiers in Handwriting Recognition, 2016Co-Authors: Kallel Faten Jaiem, Kanoun Slim, Eglin VéroniqueAbstract:Existing works on the font recognition and based on Texture Analysis often used Gray Level Cooccurence Matrix (GLCM), Gabor Filters (GF) and wavelet. In this paper, we use Steerable Pyramid (SP) for Texture Analysis of arabic homogeneous and normalized text block in order to font recognition. In this frameworks, we use K Nearest Neighbors (KNN) and Back-propagation Artificial Neural Network (BpANN) for classification. The Obtained experimental results on the APTID/MF database (Arabic Printed Text Image/ Multi- Font) are encouragents.
André Ricardo Backes - One of the best experts on this subject based on the ideXlab platform.
-
color Texture Analysis based on fractal descriptors
Pattern Recognition, 2012Co-Authors: André Ricardo Backes, Dalcimar Casanova, Odemir Martinez BrunoAbstract:Color Texture classification is an important step in image segmentation and recognition. The color information is especially important in Textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color Texture Analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a Texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color Texture Analysis methods.
-
Texture Analysis based on maximum contrast walker
Pattern Recognition Letters, 2010Co-Authors: André Ricardo Backes, Alexandre Souto Martinez, Odemir Martinez BrunoAbstract:Recently, the deterministic tourist walk has emerged as a novel approach for Texture Analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional Texture Analysis methods in the classification of a set of Brodatz Textures and their rotated versions, thus confirming the potential of the method as a feasible Texture Analysis methodology.
Andrzej Materka - One of the best experts on this subject based on the ideXlab platform.
-
Texture Analysis methodologies for magnetic resonance imaging.
Dialogues in clinical neuroscience, 2004Co-Authors: Andrzej MaterkaAbstract:Methods for the Analysis of digital-image Texture are reviewed. The functions of MaZda, a computer program for quantitative Texture Analysis developed within the framework of the European COST (Cooperation in the Field of Scientific and Technical Research) B11 program, are introduced. Examples of Texture Analysis in magnetic resonance images are discussed.
-
Texture Analysis Methods - A Review
Technical university of lodz institute of electronics COST B11 report Brussels, 1998Co-Authors: Andrzej Materka, Michal StrzeleckiAbstract:Methods for digital-image Texture Analysis are reviewed based on available literature and research work either carried our or supervised by the authors. The review has been prepared on request of Dr. Richard Lerski, Chairman of the Management Committee of the COST B11 action "Quantitation of Magnetic Resonance Image Texture".
Patrick Reuze - One of the best experts on this subject based on the ideXlab platform.
-
CVRMed - MRI Texture Analysis Applied to Trabecular Bone: An Experimental Study
Lecture Notes in Computer Science, 1995Co-Authors: Johanne Bezy-wendling, Alain Bruno, Patrick ReuzeAbstract:This paper is aimed at showing the potential interest of Texture Analysis in Magnetic Resonance images of tissues. In the first section, the Texture Analysis methods are briefly described: morphological granulometry and the Run Length method. The first one is applied to in vivo images of the wrist and the second one to ex vivo images of vertebrae, in order to characterize the trabecular bone structure. Texture Analysis allows to assess information on the trabeculae thicknesses and the sizes of the inter-trabeculae spaces.
