Choice of a pertinent color space for color texture characterization using parametric spectral analysis

2011 ◽  
Vol 44 (1) ◽  
pp. 16-31 ◽  
Author(s):  
Imtnan-Ul-Haque Qazi ◽  
Olivier Alata ◽  
Jean-Christophe Burie ◽  
Ahmed Moussa ◽  
Christine Fernandez-Maloigne
Keyword(s):  
Spectral Analysis ◽  
Color Space ◽  
Texture Characterization ◽  
Color Texture

Influence of normalization and color space to color texture classification

2017 ◽  
Vol 61 ◽  
pp. 120-138 ◽  
Author(s):  
E. Cernadas ◽  
M. Fernández-Delgado ◽  
E. González-Rufino ◽  
P. Carrión
Keyword(s):  
Texture Classification ◽  
Color Space ◽  
Color Texture

Wavelet correlation signatures for color texture characterization

1999 ◽  
Vol 32 (3) ◽  
pp. 443-451 ◽  
Author(s):  
G. Van de Wouwer ◽  
P. Scheunders ◽  
S Livens ◽  
D Van Dyck
Keyword(s):  
Texture Characterization ◽  
Color Texture

scholarly journals Multilayer complex network descriptors for color–texture characterization

2019 ◽  
Vol 491 ◽  
pp. 30-47 ◽  
Author(s):  
Leonardo F.S. Scabini ◽  
Rayner H.M. Condori ◽  
Wesley N. Gonçalves ◽  
Odemir M. Bruno
Keyword(s):  
Complex Network ◽  
Texture Characterization ◽  
Color Texture

scholarly journals Organic Boundary Location Based on Color-Texture of Visual Perception in Wireless Capsule Endoscopy Video

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Chengliang Wang ◽  
Zhuo Luo ◽  
Xiaoqi Liu ◽  
Jianying Bai ◽  
Guobin Liao
Keyword(s):  
Visual Perception ◽  
Capsule Endoscopy ◽  
Color Space ◽  
Wireless Capsule Endoscopy ◽  
Support Vector ◽  
Svm Classifier ◽  
Phase Congruency ◽  
Region Detection ◽  
Wireless Capsule ◽  
Color Texture

This paper addresses the problem of automatically locating the boundary between the stomach and the small intestine (the pylorus) in wireless capsule endoscopy (WCE) video. For efficient image segmentation, the color-saliency region detection (CSD) method is developed for obtaining the potentially valid region of the frame (VROF). To improve the accuracy of locating the pylorus, we design the Monitor-Judge model. On the one hand, the color-texture fusion feature of visual perception (CTVP) is constructed by grey level cooccurrence matrix (GLCM) feature from the maximum moments of the phase congruency covariance and hue-saturation histogram feature in HSI color space. On the other hand, support vector machine (SVM) classifier with the CTVP feature is utilized to locate the pylorus. The experimental results on 30 real WCE videos demonstrate that the proposed location method outperforms the related valuable techniques.

Color spectral analysis for spatial structure characterization of textures in IHLS color space

2010 ◽  
Vol 43 (3) ◽  
pp. 663-675 ◽  
Author(s):  
Imtnan-Ul-Haque Qazi ◽  
Olivier Alata ◽  
Jean-Christophe Burie ◽  
Christine Fernandez-Maloigne
Keyword(s):  
Spectral Analysis ◽  
Spatial Structure ◽  
Color Space ◽  
Structure Characterization
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