8.8.7 Statistical Texture Classification

Chapter Contents (Back)
Texture, Statistical.

Rosenfeld, A.,
Automatic Recognition of Basic Terrain Types from Aerial Photographs,
PhEng(28), March 1962, pp. 639-646. BibRef 6203

Abend, K., Harley, T.J., and Kanal, L.N.,
Classification of Binary Random Patterns,
IT(11), No. 4, October 1965, pp. 538-544. (Or Hartley??) BibRef 6510

Harley, T.J., and Kanal, L.N.,
Recognizing Patterns in Photographs,
AppOpt(4), No. 10, October 1965, pp. 1350. BibRef 6510

Kruger, R.P., Thompson, W.B., and Turner, A.F.,
Computer Diagnosis of Pneumoconiosis,
SMC(4), No. 1, 1974, pp. 40-49. BibRef 7400

Panda, D.P., Rosenfeld, A.,
Image Segmentation by Pixel Classification in (gray level, edge value) space,
TC(27), 1978, pp. 875-879. BibRef 7800

Rom, R.,
Distribution of Runs in Binary Words,
TC(27), 1978, pp. 1087-1089. BibRef 7800

Kidode, M., and Wechsler, H.,
A Random Walk Procedure for Texture Discrimination,
PAMI(1), No. 3, July 1979, pp. 272-280. BibRef 7907
And: Correction: PAMI(1), No. 4, October 1979, pp. 417. BibRef

Lumia, R.[Ronald], Haralick, R.M.[Robert M.], Zuniga, O.A.[Oscar A.], Shapiro, L.G.[Linda G.], Pong, T.C.[Ting-Chuen], and Wang, F.P.[Far-Peing],
Texture Analysis of Aerial Photographs,
PR(16), No. 1, 1983, pp. 39-46.
Elsevier DOI A complete analysis system that starts with a basic segmentation and the classifies the regions based on texture parameters using decision theory and clustering of statistical data. A classification is large versus small building textures. The results are not easy to judge, some were good others were not. Interesting results in terms of the style of research. BibRef 8300

Vickers, A.L., and Modestino, J.W.,
A Maximum Likelihood Approach to Texture Classification,
PAMI(4), No. 1, January 1982, pp. 61-68. BibRef 8201

Modestino, J.W., Fries, R.W., and Vickers, A.L.,
Texture Discrimination Based upon an Assumed Stochastic Texture Model,
PAMI(3), No. 5, September 1981, pp. 557-580. BibRef 8109

de Souza, P.[Peter],
A Note on a Random-Walk Model for Texture Analysis,
PR(16), No. 2, 1983, pp. 219-222.
Elsevier DOI relates to chi square test of homogeneity.
See also Random Walk Procedure for Texture Discrimination, A. BibRef 8300

Percus, J.K.,
On the Wechsler de_Souza discussion,
PR(16), No. 2, 1983, pp. 269-270.
Elsevier DOI 0309

See also Random Walk Procedure for Texture Discrimination, A. BibRef

Harwood, D.[David], Subbarao, M.[Muralidhara], Davis, L.S.[Larry S.],
Texture Classification by Local Rank Correlation,
CVGIP(32), No. 3, December 1985, pp. 404-411.
Elsevier DOI BibRef 8512

Frost, V.S., Yurovsky, L.S.,
Maximum Likelihood Classification of Synthetic Aperture Radar Imagery,
CVGIP(32), No. 3, December 1985, pp. 291-313.
Elsevier DOI BibRef 8512

Unser, M.,
Sum and Difference Histograms for Texture Classification,
PAMI(8), No. 1, January 1986, pp. 118-125. BibRef 8601

Unser, M.,
Local Linear Transforms for Texture Measurements,
SP(11), No 1, July 1986, pp. 61-79. BibRef 8607

Unser, M., and Ade, F.,
Feature Extraction and Decision Procedure for Automated Inspection of Textured Materials,
PRL(2), No. 2, March 1984, pp. 165-191. BibRef 8403

Wong, A.K.C., Shen, H.C., Wong, P.W.,
Search-Effective Multi-Class Texture Classification,
PRAI(4), 1990, pp. 527-552. BibRef 9000

Weszka, J.S., Dyer, C.R., and Rosenfeld, A.,
A Comparative Study of Texture Measures for Terrain Classification,
SMC(6), No. 4, April 1976, pp. 269-286. BibRef 7604
And: UMD-CS-TR-361, March 1975. BibRef
And: CGPR75(62-64). Evaluation, Texture. Histogram flattening; statistical classification methods; features Fourier ring/sector; fine detail paired with coarse detail performed best (?) contrast (co-occurrence); difference of average and co-occurrence better than Fourier. Co-occurrence: contrast, ASM, entropy, correlation. Difference of averages, 8H, and 8V. Gray level runlength.
See also Theoretical Comparison of Texture Algorithms, A. for a comparison of the same from a theoretical standpoint. BibRef

Dyer, C.R.[Charles R.], Weszka, J.S., and Rosenfeld, A.,
Experiments in Terrain Classification on Landsat Imagery by Texture Analysis,
UMD-CS-TR-383, ENG74-22006, June 1975. Same set of features, but using the knowledge of what works; means of the difference histogram; difference of averages. BibRef 7506

Lau, A.S.K.,
Knowledge Based and Statistical Techniques Applied to Textural Image Classifications,
PRL(6), 1987, pp. 95-100. BibRef 8700

Cohen, P., Le Dinh, C.T., Lacasse, V.,
Classification of Natural Textures by Means of Two-Dimensional Orthogonal Masks,
ASSP(37), 1989, pp. 125-128. BibRef 8900

Li, W.[Wei], Haese-Coat, V.[Veronique], Ronsin, J.[Joseph],
Residues of Morphological Filtering by Reconstruction for Texture Classification,
PR(30), No. 7, July 1997, pp. 1081-1093.
Elsevier DOI 9707
Robust Morphological Features for Texture Classification,
ICIP96(III: 173-176).

Wang, D.M., Haese-Coat, V., Bruno, A., Ronsin, J.,
Texture Classification and Segmentation Based on Iterative Morphological Decomposition,
JVCIR(4), 1993, pp. 197-214. BibRef 9300

You, J., Cohen, H.A.,
Classification and Segmentation of Rotated and Scaled Textured Images Using Texture 'Tuned' Masks,
PR(26), No. 2, February 1993, pp. 245-258.
Elsevier DOI BibRef 9302

Zhuang, C., Dunn, S.,
The Amplitude Varying Rate Statistical Approach for Texture Classification,
PRL(11), 1990, pp. 143-149. BibRef 9000

Mao, J.C.[Jian-Chang], Jain, A.K.[Anil K.],
Texture Classification and Segmentation Using Multiresolution Simultaneous Autoregressive Models,
PR(25), No. 2, February 1992, pp. 173-188.
Elsevier DOI BibRef 9202

Tsatsanis, M.K., and Giannakis, G.B.,
Object and Texture Classification Using Higher Order Statistics,
PAMI(14), No. 7, July 1992, pp. 733-750.
IEEE DOI BibRef 9207

Cohen, H.A., You, J.,
A Multi-Resolution Texture Classifier Based on Multi-Resolution Tuned Mask,
PRL(13), 1992, pp. 599-604. BibRef 9200

Bie, C.Y.C., Shen, H.C., Chiu, D.K.Y.,
Hierarchical Maximum Entropy Partitioning in Texture Image Analysis,
PRL(14), 1993, pp. 421-429. BibRef 9300

Strand, J.[Jarle], Taxt, T.[Torfinn],
Local Frequency Features for Texture Classification,
PR(27), No. 10, October 1994, pp. 1397-1406.
Elsevier DOI BibRef 9410

Hu, Y., Dennis, T.J.,
Textured Image Segmentation by Context Enhanced Clustering,
VISP(141), No. 6, December 1994, pp. 413-421. BibRef 9412

Chen, Y.Q.[Yan Qiu], Nixon, M.S.[Mark S.], Thomas, D.W.[David W.],
Statistical Geometrical Features For Texture Classification,
PR(28), No. 4, April 1995, pp. 537-552.
Elsevier DOI BibRef 9504
Texture classification using statistical geometrical features,
ICIP94(III: 446-450).

Ojala, T.[Timo], Pietikäinen, M.[Matti], Harwood, D.[David],
A Comparative Study of Texture Measures with Classification Based on Feature Distributions,
PR(29), No. 1, January 1996, pp. 51-59.
Elsevier DOI Evaluation, Texture. BibRef 9601
Performance Evaluation of Texture Measures with Classification Based on Kullback Discrimination of Distributions,

Cohen, B.[Boaz], Dinstein, I.[Its'Hak], Eyal, M.[Moshe],
A System for Computerized Classification of Color Textured Perthite Images,
PR(30), No. 9, September 1997, pp. 1533-1545.
Elsevier DOI 9708
Computerized Classification of Color Textured Perthite Images,
ICPR96(II: 601-605).
(Ben Gurion Univ. of Negev, IL) BibRef

Sziranyi, T.[Tamas], Csapodi, M.[Marton],
Texture Classification and Segmentation by Cellular Neural Networks Using Genetic Learning,
CVIU(71), No. 3, September 1998, pp. 255-270.
DOI Link BibRef 9809
Texture classification by cellular neural network and genetic learning,

Kurosu, T., Uratsuka, S., Maeno, H., Kozu, T.,
Texture Statistics for Classification of Land Use with Multitemporal JERS-1 SAR Single-Look Imagery,
GeoRS(37), No. 1, January 1999, pp. 227.
IEEE Top Reference. BibRef 9901

Thyagarajan, K.S., Nguyen, T., Persons, C.E.,
Maximum likelihood approach to image texture and acoustic signal classification,
VISP(146), No. 1, February 1999, pp. 34. BibRef 9902
A maximum likelihood approach to texture classification using wavelet transform,
ICIP94(II: 640-644).

Goon, A.A.[Alexei A.], Rolland, J.P.[Jannick P.],
Texture classification based on comparison of second-order statistics. I. Two-point probability density function estimation and distance measure,
JOSA-A(16), No. 7, July 1999, pp. 1566-1574. BibRef 9907

Chou, W.S.[Wen-Shou],
Classifying image pixels into shaped, smooth, and textured points,
PR(32), No. 10, October 1999, pp. 1697-1706.
Elsevier DOI BibRef 9910

Pietikäinen, M.[Matti], Ojala, T.[Timo], Xu, Z.L.[Ze-Lin],
Rotation-Invariant Texture Classification Using Feature Distributions,
PR(33), No. 1, January 2000, pp. 43-52.
Elsevier DOI 0005
Earlier: A1, A3, A2: SCIA97(xx-yy)
HTML Version. 9705

Öztürk, Y.[Yusuf], Abut, H.[Hüseyin],
SOAR: System of associative relations,
SP:IC(17), No. 3, March 2002, pp. 261-276.
Elsevier DOI 0202
Associative memory to model pairwise pixel interactions. BibRef

Jenssen, R., Eltoft, T.,
Independent component analysis for texture segmentation,
PR(36No. 10, October 2003, pp. 2301-2315.
Elsevier DOI 0308

Mitra, P.[Pabitra], Shankar, B.U.[B. Uma], Pal, S.K.[Sankar K.],
Segmentation of multispectral remote sensing images using active support vector machines,
PRL(25), No. 9, 2 July 2004, pp. 1067-1074.
Elsevier DOI 0407

Pal, S.K.[Sankar K.], Shankar, B.U.[B. Uma], Mitra, P.[Pabitra],
Granular computing, rough entropy and object extraction,
PRL(26), No. 16, December 2005, pp. 2509-2517.
Elsevier DOI 0512

Xia, Y.[Yong], Feng, D.D.[David Dagan], Wang, T.J.[Tian-Jiao], Zhao, R.C.[Rong-Chun], Zhang, Y.N.[Yan-Ning],
Image segmentation by clustering of spatial patterns,
PRL(28), No. 12, 1 September 2007, pp. 1548-1555.
Elsevier DOI 0707
Image segmentation; Image texture analysis; Spatial pattern; Fuzzy clustering BibRef

Ma, L.[Li], Staunton, R.C.,
A modified fuzzy C-means image segmentation algorithm for use with uneven illumination patterns,
PR(40), No. 11, November 2007, pp. 3005-3011.
Elsevier DOI 0707
Fuzzy clustering; Image segmentation; Biased illumination field; Illumination pattern; Projected pattern BibRef

Shafei, B.[Behrang], Steidl, G.[Gabriele],
Segmentation of images with separating layers by fuzzy c-means and convex optimization,
JVCIR(23), No. 4, May 2012, pp. 611-621.
Elsevier DOI 1205
Segmentation; Fuzzy-c means; TV-functional; ADMM; Convex optimization; Materials with layers BibRef

Ciak, R., Shafei, B.[Behrang], Steidl, G.[Gabriele],
Homogeneous Penalizers and Constraints in Convex Image Restoration,
JMIV(47), No. 3, November 2013, pp. 210-230.
Springer DOI 1309

Kaur, P.[Prabhjot], Soni, A.K., Gosain, A.[Anjana],
Retracted Paper: A robust kernelized intuitionistic fuzzy c-means clustering algorithm in segmentation of noisy medical images,
PRL(34), No. 2, 15 January 2013, pp. 163-175.
Elsevier DOI 1212
And: Retraction Notice: PRL(34), No. 6, 15 April 2013, pp. 709.
Elsevier DOI 1303

Akinin, M.V., Akinina, N.V., Klochkov, A.Y., Nikiforov, M.B., Sokolova, A.V.,
Fuzzy C-Means Algorithm for Segmentation of Aerial Photography Data Obtained Using Unmanned Aerial Vehicle,
DOI Link 1508

Florin, C.[Charles], Paragios, N.[Nikos], Funka-Lea, G.[Gareth], Williams, J.[James],
Time-Varying Linear Autoregressive Models for Segmentation,
ICIP07(I: 509-512).

Ma, B.[Bo], Chi, Z.[Zheru],
Texture image segmentation based on entropy theory,
ICARCV04(I: 103-108).

Sanei, S., Lee, T.K.M.,
A semi-supervised support vector machine for texture segmentation,
ICIP04(I: 223-226).

Hamdan, H.M., Larson, L.M.,
Texture classification through level lines,
ICIP02(III: 937-940).

Fan, G.L.[Guo-Liang], Song, X.M.[Xiao-Mu],
A study of contextual modeling and texture craracterization for multiscale bayesian segmentation,
ICIP02(III: 309-312).

Liu, F.[Fei], Song, X., Luo, Y., Hu, D.,
Unsupervised Mumford-Shah energy based hybrid of texture and nontexture image segmentation,
ICIP02(II: 753-756).

Roula, M.A., Bouridane, A., Kurugollu, F., Amira, A.,
Unsupervised segmentation of multispectral images using edge progression and cost function,
ICIP02(III: 781-784).

Roula, M.A., Bouridane, A., Amira, A., Sage, P., Milligan, P.,
A Novel Technique for Unsupervised Texture Segmentation,
ICIP01(I: 58-61).

Tian, B., Azimi-Sadjadi, M.R., Vonder Haar, T., and Reinke, D.,
Neural Network-Based Cloud Classification on Satellite Imagery Using Textural Features,
ICIP97(III: 209-212).
IEEE DOI BibRef 9700

Hepplewhite, L., Stonham, T.J.,
Unsupervised Texture Segmentation by Hebbian Learnt Cortical Cells,
ICPR96(IV: 381-385).
(Brunel Univ., UK) BibRef

Runnacles, B.S.[Ben S.], Nixon, M.S.[Mark S.],
Texture Extraction and Segmentation via Statistical Geometric Features,
ICIP96(III: 129-132).
IEEE DOI BibRef 9600

Ohm, J.R., and Ma, P.,
Feature-Based Cluster Segmentation of Image Sequences,
ICIP97(III: 178-181).
IEEE DOI BibRef 9700

Kaplan, L.M., and Murenzi, R.,
Texture Segmentation Using Multiscale Hurst Features,
ICIP97(III: 205-208).
IEEE DOI BibRef 9700

Kuan, J.K.P.[Joseph K.P.], and Lewis, P.H.[Paul H.],
Complex Texture Classification Using Edge Information,
Visual97(xx). BibRef 9700

Shen, J.[Jun], Sun, H.[Huaijiang], and Yang, J.Y.[Jing-Yu],
Fuzzy Neural Nets with Asymmetric Pi Membership Functions and Application to Texture Classification,
HTML Version. 9705

Negi, A.[Atul], Sreedevi, P., Debbarma, P.,
Unsupervised texture segmentation using Hermite transform filters,
Springer DOI 9709

Horng, M.H., Sun, Y.N., Lin, X.Z.,
Texture Feature Coding Method for Classification of Liver Sonography,
Springer DOI Gray-level gradient variations in 3X3 region. BibRef 9600

Potlapalli, H.[Harsh], and Luo, R.C.[Ren C.],
Fractal Based Classification of Natural Textures,
ARPA94(II:1595-1606). BibRef 9400

Dasarathy, B.V.,
Texture Based Classification of Cell Imagery,
SPIE(1652), Medical Imaging VI: Image Processing, February 1992, pp. 284-291. BibRef 9202

Dasarathy, K.B., Chittur, K.K., and Dasarathy, B.V.,
Analysis of Skin Oil by FTIR Spectroscopy,
SPIE(2847), August 1996, pp. 67-77. BibRef 9608

Hepplewhite, L., Stonham, T.,
Texture Classification Using N-Tuple Pattern Recognition,
ICPR96(IV: 159-163).
(Brunel Univ., UK) BibRef

Reed, T.R., Wechsler, H.,
Texture Analysis and Clustering Using the Wigner Distribution,
ICPR88(II: 770-772).
IEEE DOI BibRef 8800

Wechsler, H.,
Feature Extraction for Texture Discrimination,
PRIP79(399-403). BibRef 7900

Hallion, A., Masson, P., Roux, C.,
A Non-Parametric Approach to Linear Feature Extraction: Application to Classification of Binary Synthetic Textures,
ICPR88(II: 1036-1039).

Chen, C.H.,
A Comparative Study of Texture Classification Using Spectral Features,
ICPR82(1074-1077). BibRef 8200

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Multi-Scale, Pyramid Texture Segmentation Approaches .

Last update:Aug 31, 2023 at 09:37:21