7.10.1 Texture Discrimination and Classification

Winkler, G., Vattrodt, K.,
Measures for Conspicuousness,
CGIP(8), No. 3, December 1978, pp. 355-368.
Elsevier DOI BibRef 7812

Pratt, W.K., Faugeras, O.D., Gagalowicz, A.,
Visual Discrimination of Stochastic Texture Fields,
SMC(8), 1978, pp. 796-804. BibRef 7800

Gagalowicz, A.,
Visual Discrimination of Stochastic Texture Fields Based upon Their Second Order Statistics,
ICPR80(786-788). BibRef 8000
Earlier:
Analysis of Texture Using a Stochastic Model,
ICPR78(541-544). BibRef

Gagalowicz, A.,
Stochastic Texture Fields Synthesis from a Priori Given Second Order Statistice,
PRIP79(376-381). BibRef 7900

Wang, S., Velasco, F.R.D., Wu, A., Rosenfeld, A.,
Relative Effectiveness of Selected Texture Primitive Statistics for Texture Discrimination,
SMC(11), 1981, pp. 360-370. BibRef 8100

Hsu, S.Y.[Shin-Yi],
The Mahalanobis Classifier with the Generalized Inverse Approach for Automated Analysis of Imagery Texture Data,
CGIP(9), No. 2, February 1979, pp. 117-134.
Elsevier DOI BibRef 7902

Hirota, K.[Kaoru],
The Bounded Variation Quantity (B.V.Q.) and its Application to Feature Extraction,
PR(15), No. 2, 1982, pp. 93-101.
Elsevier DOI 0309
BibRef

Liu, S.S.[Song-Sheng], Jernigan, M.E.,
Texture Analysis and Discrimination in Additive Noise,
CVGIP(49), No. 1, January 1990, pp. 52-67.
Elsevier DOI BibRef 9001

Greenspan, H., Goodman, R., Chellappa, R., Anderson, C.H.,
Learning Texture-Discrimination Rules in a Multiresolution System,
PAMI(16), No. 9, September 1994, pp. 894-901.
IEEE DOI BibRef 9409

Malik, J., Perona, P.,
Preattentive Texture Discrimination with Early Vision Mechanism,
JOSA-A(7), No. 5, May 1990, pp. 923-932. BibRef 9005
Earlier:
A Computational Model of Texture Perception,
UCBCSD-89-491, 1989. BibRef
And:
A Computational Model of Texture Segmentation,
CVPR89(326-332).
IEEE DOI
See also Deformable Kernels for Early Vision. BibRef

Lovell, R.[Robb], Uttal, W.R.[William R.], Shepherd, T.[Thomas], Dayanand, S.[Sriram],
A Model of Visual Texture Discrimination Using Multiple Weak Operators and Spatial Averaging,
PR(25), No. 10, October 1992, pp. 1157-1170.
Elsevier DOI BibRef 9210

He, D.C.[Dong-Chien], Wang, L.[Li], Guibert, J.[Jean],
Texture Discrimination Based on an Optimal Utilization of Texture Features,
PR(21), No. 2, 1988, pp. 141-146.
Elsevier DOI 0309
BibRef

Thomson, M.G.A., Foster, D.H.,
Role of Second-Order and Third-Order Statistics in the Discriminability of Natural Images,
JOSA-A(14), No. 9, September 1997, pp. 2081-2090. 9709
BibRef

Yuille, A.L., Coughlan, J.M.[James M.], Wu, Y.N.[Ying-Nian], Zhu, S.C.[Song Chun],
Order Parameters for Detecting Target Curves in Images: When Does High Level Knowledge Help?,
IJCV(41), No. 1-2, January-February 2001, pp. 9-33.
DOI Link Bayesian inference, curve detection, order parameters, minimax entropy Generalize earlier
See also Fundamental Limits of Bayesian Inference: Order Parameters and Phase Transitions for Road Tracking. 0105
BibRef

Yuille, A.L., Coughlan, J.M.[James M.], Zhu, S.C.[Song Chun], Wu, Y.N.[Ying-Nian],
Order Parameters for Minimax Entropy Distributions: When does High Level Knowledge Help?,
CVPR00(I: 558-565).
IEEE DOI 0005
Choose the model BibRef

Coughlan, J.M.[James M.], Yuille, A.L.[Alan L.],
G-factors: Relating Distributions on Features to Distributions on Images,
SCTV01(xx-yy). 0106
BibRef

Kim, K.I., Park, S.H., Kim, H.J.,
Kernel Principal Component Analysis for Texture Classification,
SPLetters(8), No. 2, February 2001, pp. 39-41.
IEEE Top Reference. 0101
BibRef

Kim, K.I.[Kwang In], Jung, K.C.[Kee-Chul], Park, S.H.[Se Hyun], Kim, H.J.[Hang Joon],
Support Vector Machines for Texture Classification,
PAMI(24), No. 11, November 2002, pp. 1542-1550.
IEEE Abstract. 0211
No feature extraction, just the gray levels. BibRef

Epifanio, I., Ayala, G.,
A random set view of texture classification,
IP(11), No. 8, August 2002, pp. 859-867.
IEEE DOI 0209
BibRef

Sánchez Yáñez, R.E.[Raúl E.], Kurmyshev, E.V.[Evguenii V.], Cuevas, F.J.[Francisco J.],
A framework for texture classification using the coordinated clusters representation,
PRL(24), No. 1-3, January 2003, pp. 21-31.
Elsevier DOI 0211
BibRef

Sánchez Yáñez, R.E.[Raúl E.], Kurmyshev, E.V.[Evguenii V.], Fernández, A.[Antonio],
One-class texture classifier in the CCR feature space,
PRL(24), No. 9-10, June 2003, pp. 1503-1511.
Elsevier DOI 0304
BibRef

Kurmyshev, E.V.[Evguenii V.], Sanchez Yanez, R.E.[Raul E.],
Comparative experiment with colour texture classifiers using the CCR feature space,
PRL(26), No. 9, 1 July 2005, pp. 1346-1353.
Elsevier DOI 0506
BibRef

Deng, H.[Huawu], Chan, K.L.[Kap Luk], Liu, J.[Jun],
The Poisson equation for image texture modelling,
PRL(24), No. 9-10, June 2003, pp. 1571-1582.
Elsevier DOI 0304
BibRef

Huang, Y.[Yong], Chan, K.L.[Kap Luk], Huang, Z.Y.[Zhong-Yang],
An Adaptive Model for Texture Classification,
ICPR00(Vol III: 893-896).
IEEE DOI 0009
BibRef

Li, S.T.[Shu-Tao], Kwok, J.T.[James T.], Zhu, H.L.[Hai-Long], Wang, Y.N.[Yao-Nan],
Texture classification using the support vector machines,
PR(36), No. 12, December 2003, pp. 2883-2893.
Elsevier DOI 0310
BibRef

Kwok, J.T.[James T.],
Support Vector Mixture for Classification and Regression Problems,
ICPR98(Vol I: 255-258).
IEEE DOI 9808
BibRef

Christodoulou, C.I., Michaelides, S.C., Pattichis, C.S.,
Multifeature texture analysis for the classification of clouds in satellite imagery,
GeoRS(41), No. 11, November 2003, pp. 2662-2668.
IEEE Abstract. 0311
BibRef

Pietikäinen, M.[Matti], Nurmela, T.[Tomi], Mäenpää, T.[Topi], Turtinen, M.[Markus],
View-based recognition of real-world textures,
PR(37), No. 2, February 2004, pp. 313-323.
Elsevier DOI 0311
BibRef

Chen, Q., Gong, P.,
Automatic Variogram Parameter Extraction for Textural Classification of the Panchromatic IKONOS Imagery,
GeoRS(42), No. 5, May 2004, pp. 1106-1115.
IEEE Abstract. 0407
Automatically extract range and sill from variogram. BibRef

Martinez Alajarin, J., Luis Delgado, J.D., Tomas Balibrea, L.M.,
Automatic system for quality-based classification of marble textures,
SMC-C(35), No. 4, November 2005, pp. 488-497.
IEEE DOI 0512
BibRef

Chen, X.W.[Xue-Wen], Zeng, X.Y.[Xiang-Yan], van Alphen, D.[Deborah],
Multi-class feature selection for texture classification,
PRL(27), No. 14, 15 October 2006, pp. 1685-1691.
Elsevier DOI 0609
Multi-class feature selection; Texture classification; Least squares support vector machine; Recursive feature elimination; Min-max value BibRef

Choy, S.K.[Siu-Kai], Tong, C.S.[Chong-Sze],
Supervised Texture Classification Using Characteristic Generalized Gaussian Density,
JMIV(29), No. 1, Septmeber 2007, pp. 35-47.
Springer DOI 0709
BibRef

Choy, S.K., Tong, C.S.,
Statistical Properties of Bit-Plane Probability Model and Its Application in Supervised Texture Classification,
IP(17), No. 8, August 2008, pp. 1399-1405.
IEEE DOI 0808

See also Fast and Effective Model for Wavelet Subband Histograms and Its Application in Texture Image Retrieval, A. BibRef

Choy, S.K., Tong, C.S.,
Statistical Wavelet Subband Characterization Based on Generalized Gamma Density and Its Application in Texture Retrieval,
IP(19), No. 2, February 2010, pp. 281-289.
IEEE DOI 1002
BibRef

Li, L., Tong, C.S.[Chong-Sze], Choy, S.K.[Siu-Kai],
Texture Classification Using Refined Histogram,
IP(19), No. 5, May 2010, pp. 1371-1378.
IEEE DOI 1004
BibRef

Shoshany, M.[Maxim],
An evolutionary patch pattern approach for texture discrimination,
PR(41), No. 7, July 2008, pp. 2327-2336.
Elsevier DOI 0804
Patch patterns; Spatial dynamics; Spatial duality; Texture discrimination BibRef

Caputo, B.[Barbara],
Class Specific Object Recognition using Kernel Gibbs Distributions,
ELCVIA(7), No. 2, 2008, pp. xx-yy.
DOI Link 0903
BibRef

Caputo, B.[Barbara], Cusano, C.[Claudio], Lanzi, M.[Martina], Napoletano, P.[Paolo], Schettini, R.[Raimondo],
On the Importance of Domain Adaptation in Texture Classification,
CIAP17(I:380-390).
Springer DOI 1711
BibRef

Caputo, B.[Barbara], Hayman, E.[Eric], Mallikarjuna, P.,
Class-Specific Material Categorisation,
ICCV05(II: 1597-1604).
IEEE DOI 0510
Decision tree, each node is a SVM to split one class from all others. BibRef

Hayman, E.[Eric], Caputo, B.[Barbara], Fritz, M.[Mario], Eklundh, J.O.[Jan-Olof],
On the Significance of Real-World Conditions for Material Classification,
ECCV04(Vol IV: 253-266).
Springer DOI 0405
SVM application. Texture recognition. Still not a solved problem in general. BibRef

Targhi, A.T.[Alireza Tavakoli], Hayman, E.[Eric], Eklundh, J.O.[Jan-Olof], Shahshahani, M.[Mehrdad],
The Eigen-Transform and Applications,
ACCV06(I:70-79).
Springer DOI 0601
Texture measure of roughness. Bottom up detection, top down segmentation. BibRef

Drbohlav, O.[Ondrej], Leonardis, A.[Ales],
Towards correct and informative evaluation methodology for texture classification under varying viewpoint and illumination,
CVIU(114), No. 4, April 2010, pp. 439-449.
Elsevier DOI 1003
Texture classification; Illumination invariance; Viewpoint invariance; Evaluation methodology; Generalization ability BibRef

Rengers, N.[Norman], Prinz, T.[Torsten],
JAVA-based Texture Analysis Employing Neighborhood Gray-Tone Difference Matrix (NGTDM) for Optimization of Land Use Classifications in High Resolution Remote Sensing Data,
PFG(2009), No. 5, 2009, pp. 455-467.
WWW Link. 1211
Code, Texture Analysis. Code, Texture Analysis, Java. BibRef

Sun, X.P.[Xiang-Ping], Wang, J.[Jin], She, M.F.H.[Mary F.H.], Kong, L.X.[Ling-Xue],
Sparse representation with multi-manifold analysis for texture classification from few training images,
IVC(32), No. 11, 2014, pp. 835-846.
Elsevier DOI 1410
Texture classification BibRef

Zhang, W., Zhang, W., Liu, K., Gu, J.,
A Feature Descriptor Based on Local Normalized Difference for Real-World Texture Classification,
MultMed(20), No. 4, April 2018, pp. 880-888.
IEEE DOI 1804
Feature extraction, Histograms, Interpolation, Lighting, Robustness, Sensitivity, Visualization, Normalized difference vector, texture representation BibRef

Huo, Z.Q.[Zhan-Qiang], Zhang, Y.Q.[Yan-Qi], Liu, H.M.[Hong-Min], Wang, J.[Jing], Liu, X.[Xin], Zhang, J.Y.[Ji-Yong],
Improved covariant local feature detector,
PRL(135), 2020, pp. 1-7.
Elsevier DOI 2006
Local feature, Image matching, Covariant features, Feature repeatability BibRef

Chen, K.X.[Kai-Xuan], Ren, J.Y.[Jie-Yi], Wu, X.J.[Xiao-Jun], Kittler, J.V.[Josef V.],
Covariance descriptors on a Gaussian manifold and their application to image set classification,
PR(107), 2020, pp. 107463.
Elsevier DOI 2008
Covariance descriptors, Riemannian local difference vector, Riemannian covariance descriptors, Image set classification
See also ETH-80 Dataset, The. BibRef

Ren, J.Y.[Jie-Yi], Wu, X.J.[Xiao-Jun], Kittler, J.V.[Josef V.],
Discriminative block-diagonal covariance descriptors for image set classification,
PRL(136), 2020, pp. 230-236.
Elsevier DOI 2008
Covariance descriptor, SPD matrix, Riemannian manifold, Image set classification BibRef

Mao, S.B.[Shang-Bo], Rajan, D.[Deepu], Chia, L.T.[Liang Tien],
Deep residual pooling network for texture recognition,
PR(112), 2021, pp. 107817.
Elsevier DOI 2102
Texture recognition, Residual pooling BibRef

Zhu, K.[Kai], Cao, Y.[Yang], Zhai, W.[Wei], Zha, Z.J.[Zheng-Jun],
One-Shot Texture Retrieval Using Global Grouping Metric,
MultMed(23), 2021, pp. 3726-3737.
IEEE DOI 2110
Image segmentation, Task analysis, Measurement, Adaptation models, Feature extraction, Semantics, Attention, texture BibRef

Zhai, W.[Wei], Cao, Y.[Yang], Zha, Z.J.[Zheng-Jun], Xie, H.[Hai_Yong], Wu, F.[Feng],
Deep Structure-Revealed Network for Texture Recognition,
CVPR20(11007-11016)
IEEE DOI 2008
Feature extraction, Phase change materials, Collaboration, Convolution, Image recognition, Task analysis BibRef

Fang, P.F.[Peng-Fei], Zhou, J.M.[Jie-Ming], Roy, S.[Soumava], Petersson, L.[Lars], Harandi, M.[Mehrtash],
Bilinear Attention Networks for Person Retrieval,
ICCV19(8029-8038)
IEEE DOI 2004
Second order statistical information. feature extraction, higher order statistics, image representation, learning (artificial intelligence), Computer architecture BibRef

Zhai, W., Cao, Y., Zhang, J., Zha, Z.,
Deep Multiple-Attribute-Perceived Network for Real-World Texture Recognition,
ICCV19(3612-3621)
IEEE DOI 2004
convolutional neural nets, feature extraction, image coding, image recognition, image texture, abstracted semantic concepts BibRef

Alonso-Cuevas, J.L.[Juan L.], Sanchez-Yanez, R.E.[Raul E.], Kurmyshev, E.V.[Evguenii V.],
Scaled CCR Histogram for Scale-Invariant Texture Classification,
MCPR18(277-286).
Springer DOI 1807
BibRef

Dai, X.Y.[Xi-Yang], Ng, J.Y.H.[Joe Yue-Hei], Davis, L.S.[Larry S.],
FASON: First and Second Order Information Fusion Network for Texture Recognition,
CVPR17(6100-6108)
IEEE DOI 1711
Architecture, Benchmark testing, Computational modeling, Computer architecture, Fuses, Training
See also TAN: Temporal Aggregation Network for Dense Multi-Label Action Recognition. BibRef

Faraki, M.[Masoud], Harandi, M.T.[Mehrtash T.], Porikli, F.M.[Fatih M.],
Image set classification by symmetric positive semi-definite matrices,
WACV16(1-8)
IEEE DOI 1606
BibRef
Earlier:
Material Classification on Symmetric Positive Definite Manifolds,
WACV15(749-756)
IEEE DOI 1503
Covariance matrices. Databases. Second order statistics. BibRef

Eberhardt, S.[Sven], Zetzsche, C.[Christoph],
Self-localization on texture statistics,
ICIP14(976-980)
IEEE DOI 1502
Cities and towns BibRef

Schaeffer, H.[Hayden], Osher, S.J.[Stanley J.],
A Low Patch-Rank Interpretation of Texture,
SIIMS(6), No. 1, 2013, pp. 226-262.
DOI Link 1304
BibRef

Chakraborty, D., Thakur, S., Jeyaram, A., Krishna Murthy, Y.V.N., Dadhwal, V.K.,
Texture Analysis for Classification of RISAT-II Images,
ISPRS12(XXXIX-B3:461-466).
DOI Link 1209
BibRef

Xu, M.Q.[Min-Qiang], Zhou, X.[Xi], Li, Z.[Zhen], Dai, B.Q.[Bei-Qian], Huang, T.S.[Thomas S.],
Extended Hierarchical Gaussianization for scene classification,
ICIP10(1837-1840).
IEEE DOI 1009
Gaussian Mixture Model in Bayesian framework. BibRef

Guermeur, P.[Philippe], Manzanera, A.[Antoine],
Image Characterization from Statistical Reduction of Local Patterns,
CIARP09(571-578).
Springer DOI 0911
BibRef

Wang, G.S.[Gui-Song], Kinser, J.M.,
Texture discrimination and classification using pulse images,
AIPR04(55-60).
IEEE DOI 0410
BibRef

Thumfart, S.[Stefan], Heidl, W.[Wolfgang], Scharinger, J.[Josef], Eitzinger, C.[Christian],
A Quantitative Evaluation of Texture Feature Robustness and Interpolation Behaviour,
CAIP09(1154-1161).
Springer DOI 0909
BibRef

Tan, X.[Xi],
Ingredient Separation of Natural Images: A Multiple Transform Domain Method Based on Sparse Coding Strategy,
ICIAR07(752-760).
Springer DOI 0708
BibRef

Zhang, P.[Peng], Peng, J.[Jing], Buckles, B.[Bill],
Learning Optimal Filter Representation for Texture Classification,
ICPR06(II: 1138-1141).
IEEE DOI 0609
BibRef

Qin, L.[Lei], Zheng, Q.F.[Qing-Fang], Jiang, S.Q.[Shu-Qiang], Huang, Q.M.[Qing-Ming], Gao, W.[Wen],
Unsupervised texture classification: Automatically discover and classify texture patterns,
IVC(26), No. 5, May 2008, pp. 647-656.
Elsevier DOI 0803
Unsupervised texture classification; NMF; PLSI; Invariant descriptor BibRef

Qin, L.[Lei], Wang, W.Q.[Wei-Qiang], Huang, Q.M.[Qing-Ming], Gao, W.[Wen],
Unsupervised Texture Classification: Automatically Discover and Classify Texture Patterns,
ICPR06(II: 433-436).
IEEE DOI 0609
BibRef

Southam, P., Harvey, R.,
Towards texture classification in real scenes,
BMVC05(xx-yy).
HTML Version. 0509
BibRef
Earlier:
Compact rotation-invariant texture classification,
ICIP04(V: 3033-3036).
IEEE DOI 0505
BibRef

Win, K.[Khin], Baik, S.[Sung], Baik, R.[Ran], Ahn, S.[Sung], Kim, S.[Sang], Jo, Y.[Yung],
Texture Feature Extraction and Selection for Classification of Images in a Sequence,
IWCIA04(750-757).
Springer DOI 0505
BibRef

Targhi, A.T.[Alireza Tavakoli], Geusebroek, J.M.[Jan-Mark], Zisserman, A.[Andrew],
Texture classification with minimal training images,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Pavan, M., Pelillo, M.,
Unsupervised texture segmentation by dominant sets and game dynamics,
CIAP03(302-307).
IEEE DOI 0310
BibRef

Jain, A.K.[Anil K.], Karu, K.[Kalle],
Texture analysis: Representation and matching,
CIAP95(2-10).
Springer DOI 9509
BibRef
Earlier:
Automatic filter design for texture discrimination,
ICPR94(A:454-458).
IEEE DOI 9410
BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Color Textures and Texture with Color .