7.10.7 Filter Approaches to Texture

Chapter Contents (Back)
Filters. Textures, Filters.
See also Local Binary Patterns, LPB for Texture.
See also Texture Segmentation Using Filters.

Apostolico, A., Caianiello, E.R., Fischetti, E., Vitulano, S.,
An Application of C-Calculus to Texture Analysis: C-Transforms,
PR(10), No. 5-6, 1978, pp. 389-396.
Elsevier DOI BibRef 7800

Caianiello, E.R., Gisolfi, A., Vitulano, S.,
A Technique for Texture Analysis Using C-Calculus,
SP(1), 1979, pp. 159-173. BibRef 7900

Wechsler, H.[Harry], Citron, T.[Todd],
Feature extraction for texture classification,
PR(12), No. 5, 1980, pp. 301-311.
Elsevier DOI 0309
BibRef

Ade, F.,
Characterization of Textures by 'Eigenfilters',
SP(5), 1983, pp. 451-457. BibRef 8300

Beck, J.[Jacob], Sutter, A.[Anne], Ivry, R.[Richard],
Spatial Frequency Channels and Perceptual Grouping in Texture Segregation,
CVGIP(37), No. 2, February 1987, pp. 299-325.
Elsevier DOI BibRef 8702

Bergen, J.R., Adelson, E.H.,
Early Vision and Texture Perception,
Nature(333), 1988, pp. 363-367. Textures are similar (to people) when similar response in a bank of filters (e.g. Gabor). BibRef 8800

Montes, J., Cristobal, G., Bescos, J.,
Texture Isolation by Adaptive Digital Filtering,
IVC(6), No. 3, August 1988, pp. 189-192.
Elsevier DOI BibRef 8808

Kundu, A.[Amlan], Chen, J.L.[Jia-Lin],
Texture Classification Using QMF Bank-Based Subband Decomposition,
GMIP(54), No. 5, September 1992, pp. 369-384. BibRef 9209

Coggins, J.M., Jain, A.K.,
A Spatial Filtering Approach to Texture Analysis,
PRL(3), 1985, pp. 195-203. BibRef 8500

He, D.C.[Dong-Chen], Wang, L.[Li],
Textural filters based on the texture spectrum,
PR(24), No. 12, 1991, pp. 1187-1195.
Elsevier DOI 0401
BibRef

Olstad, B.[Bjørn],
Reasoning with entropy graphs for image operators,
PR(26), No. 8, August 1993, pp. 1255-1275.
Elsevier DOI 0401
Structuring of large sets of image operators. For Segmentation. BibRef

Shang, C.J.[Chang-Jing], Brown, K.[Keith],
Principal features-based texture classification with neural networks,
PR(27), No. 5, May 1994, pp. 675-687.
Elsevier DOI 0401
BibRef

Linnett, L.M., Carmichael, D.R., Clarke, S.J.,
Texture Classification Using a Spatial-Point Process Model,
VISP(142), No. 1, February 1995, pp. 1-6. BibRef 9502

Francos, J.M., Meiri, A.Z., Porat, B.,
A Unified Texture Model Based on a 2-D Wold Like Decomposition,
TSP(41), August 1993, pp. 2665-2678. BibRef 9308
Earlier: A1, A2, Only:
A unified structural-stochastic model for texture analysis and synthesis,
ICPR88(I: 41-45).
IEEE DOI 8811
BibRef

Francos, J.M., Narasimhan, A., Woods, J.W.,
Maximum likelihood parameter estimation of textures using a Wold-decomposition based model,
IP(4), No. 12, December 1995, pp. 1655-1666.
IEEE DOI 0402
BibRef

Sriram, R., Francos, J.M., Pearlman, W.A.,
Texture Coding Using a Wold Decomposition Model,
IP(5), No. 9, September 1996, pp. 1382-1386.
IEEE DOI BibRef 9609
Earlier: ICPR94(C:35-39).
IEEE DOI 9410
BibRef

Chen, J.L.[Jia-Lin], Kundu, A.,
Rotation and gray scale transform invariant texture identification using wavelet decomposition and hidden Markov model,
PAMI(16), No. 2, February 1994, pp. 208-214.
IEEE DOI Wavelets. Markov Model. BibRef 9402

Chen, J.L., Kundu, A.,
Unsupervised Texture Segmentation Using Multichannel Decomposition and Hidden Markov-Models,
IP(4), No. 5, May 1995, pp. 603-619.
IEEE DOI BibRef 9505
Earlier:
Automatic Unsupervised Texture Segmentation Using Hidden Markov Model,
ICASSP93(V: 21-24). BibRef

Hall, T.E., Giannakis, G.B.,
Image Modeling Using Inverse Filtering Criteria with Application to Textures,
IP(5), No. 6, June 1996, pp. 938-949.
IEEE DOI 9607
BibRef
Earlier:
Image modeling using inverse filtering criteria with application to texture images,
ICIP94(III: 392-396).
IEEE DOI 9411
BibRef

Hall, T.E., Giannakis, G.B.,
Bispectral analysis and model validation of texture images,
IP(4), No. 7, July 1995, pp. 996-1009.
IEEE DOI 0402
BibRef

Manian, V.[Vidya], Vasquez, R.[Ramon],
Scaled and rotated texture classification using a class of basis functions,
PR(31), No. 12, December 1998, pp. 1937-1948.
Elsevier DOI BibRef 9812

Cristobal, G.[Gabriel], Hormigo, J.[Javier],
Texture segmentation through eigen-analysis of the Pseudo-Wigner distribution,
PRL(20), No. 3, March 1999, pp. 337-345. BibRef 9903

Chen, C.C.[Chien-Chang], Chen, C.C.[Chaur-Chin],
Filtering methods for texture discrimination,
PRL(20), No. 8, August 1999, pp. 783-790. BibRef 9908

Manian, V., Vasquez, R., Katiyar, P.,
Texture Classification Using Logical Operators,
IP(9), No. 10, October 2000, pp. 1693-1703.
IEEE DOI 0010
BibRef

Bisoi, A.K.[Ajay Kumar], Mishra, J.[Jibitesh],
On calculation of fractal dimension of images,
PRL(22), No. 6-7, May 2001, pp. 631-637.
Elsevier DOI 0105
BibRef

Bresch, M.[Manfred],
Optimizing filter banks for supervised texture recognition,
PR(35), No. 4, April 2002, pp. 783-790.
Elsevier DOI 0201
BibRef

Barsky, S.[Svetlana], Petrou, M.[Maria],
On the Reliability of Computing Wigner Texture Features,
JMIV(16), No. 2, March 2002, pp. 107-129.
DOI Link 0202
BibRef

Zhu, S.C.[Song Chun], Liu, X.W.[Xiu-Wen],
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?,
PAMI(24), No. 7, July 2002, pp. 1001-1006.
IEEE Abstract. 0207
BibRef
Earlier: CVPR00(II: 2-9).
IEEE DOI 0005
Identify 2 issues: efficience in liklihood functions and variance in approximating partitions functions.
See also Minimax Entropy Principles and Its Application to Texture Modeling. BibRef

Huang, Y.[Yong], Chan, K.L.[Kap Luk], Zhang, Z.H.[Zhi-Hua],
Texture classification by multi-model feature integration using Bayesian networks,
PRL(24), No. 1-3, January 2003, pp. 393-401.
Elsevier DOI 0211
BibRef

Li, Y.[Yan], Peng, J.X.[Jia-Xiong],
Remote Sensing Texture Analysis Using Multi-Parameter and Multi-Scale Features,
PhEngRS(69), No. 4, April 2003, pp. 351-356. The new feature set, derived from fractional Brownian motion, is presented.
WWW Link. 0304
BibRef

Nunes, J.C., Bouaoune, Y., Delechelle, E., Niang, O., Bunel, P.,
Image analysis by bidimensional empirical mode decomposition,
IVC(21), No. 12, November 2003, pp. 1019-1026.
Elsevier DOI 0310
EMD (empirical mode decomposition) from Huang. Apply to texture extraction and image filtering. Multiple scales. BibRef

Nunes, J.C.[Jean Claude], Guyot, S., Deléchelle, E.[Eric],
Texture analysis based on local analysis of the Bidimensional Empirical Mode Decomposition,
MVA(16), No. 3, May 2005, pp. 177-188.
Springer DOI 0505
BibRef

Nunes, J.C.[Jean Claude], Niang, O.[Oumar], Bouaoune, Y.[Yasmina], Delechelle, E.[Eric], Bunel, P.[Philippe],
Bidimensional Empirical Mode Decomposition Modified for Texture Analysis,
SCIA03(171-177).
Springer DOI 0310
BibRef

Varma, M.[Manik], Zisserman, A.[Andrew],
A Statistical Approach to Texture Classification from Single Images,
IJCV(62), No. 1-2, April-May 2005, pp. 61-81.
DOI Link 0411
BibRef
Earlier:
Texture classification: are filter banks necessary?,
CVPR03(II: 691-698).
IEEE DOI 0307
BibRef
And:
Classifying Images of Materials: Achieving Viewpoint and Illumination Independence,
ECCV02(III: 255 ff.).
Springer DOI 0205
Texture classification. Clustered filter responses. Compared to: Leung and Malik (
See also Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons. ), Schmid (
See also Constructing Models for Content-Based Image Retrieval. ) and Cula and Dana (
See also 3D Texture Recognition Using Bidirectional Feature Histograms. ), BibRef

Varma, M.[Manik], Zisserman, A.[Andrew],
A Statistical Approach to Material Classification Using Image Patch Exemplars,
PAMI(31), No. 11, November 2009, pp. 2032-2047.
IEEE DOI 0910
For material categories. BibRef

Varma, M.[Manik], Zisserman, A.[Andrew],
Unifying statistical texture classification frameworks,
IVC(22), No. 14, 1 December 2004, pp. 1175-1183.
Elsevier DOI 0412
BibRef

Chantler, M.J., Petrou, M., Penirsche, A., Schmidt, M., McGunnigle, G.,
Classifying Surface Texture while Simultaneously Estimating Illumination Direction,
IJCV(62), No. 1-2, April-May 2005, pp. 83-96.
DOI Link 0411
BibRef

Penirsche, A., Chantler, M.J., Petrou, M.,
Illuminant Rotation Invariant Classification of 3D Surface Textures using Lissajous`s Ellipses,
Texture02(103-108). 0207
BibRef

Chantler, M.J., Schmidt, M., Petrou, M., McGunnigle, G.,
The Effect of Illuminant Rotation on Texture Filters: Lissajous's Ellipses,
ECCV02(III: 289 ff.).
Springer DOI 0205
BibRef

Dong, X.H.[Xing-Hui], Chantler, M.J.[Mike J.],
Perceptually Motivated Image Features Using Contours,
IP(25), No. 11, November 2016, pp. 5050-5062.
IEEE DOI 1610
BibRef
Earlier:
Texture Similarity Estimation Using Contours,
BMVC14(xx-yy).
HTML Version. 1410
BibRef
Earlier:
The Importance of Long-Range Interactions to Texture Similarity,
CAIP13(425-432).
Springer DOI 1308
higher order statistics BibRef

Clarke, A.[Alasdair], Halley, F.[Fraser], Newell, A.J.[Andrew J.], Griffin, L.D.[Lewis D.], Chantler, M.J.[Mike J.],
Perceptual Similarity: A Texture Challenge,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Gluckman, J.M.[Joshua M.],
Visually Distinct Patterns with Matching Subband Statistics,
PAMI(27), No. 2, February 2005, pp. 252-264.
IEEE Abstract. 0501
BibRef
Earlier:
On the use of marginal statistics of subband images,
ICCV03(448-455).
IEEE DOI 0311
BibRef
And:
Gradient field distributions for the registration of images,
ICIP03(II: 691-694).
IEEE DOI 0312
Analyze ability of various filters to distinguish different stimuli. When statistics are the same. BibRef

Knutsson, H.[Hans], Andersson, M.[Mats],
Implications of invariance and uncertainty for local structure analysis filter sets,
SP:IC(20), No. 6, July 2005, pp. 569-581.
Elsevier DOI 0506
BibRef

Bocher, P.K., McCloy, K.R.,
The Fundamentals of Average Local Variance: Part I: Detecting Regular Patterns,
IP(15), No. 2, February 2006, pp. 300-310.
IEEE DOI 0602
Mean and StDev of 3X3 window. BibRef

Bocher, P.K., McCloy, K.R.,
The Fundamentals of Average Local Variance: Part II: Sampling Simple Regular Patterns With Optical Imagery,
IP(15), No. 2, February 2006, pp. 311-318.
IEEE DOI 0602
BibRef

Petrou, M., Piroddi, R., Talebpour, A.,
Texture recognition from sparsely and irregularly sampled data,
CVIU(102), No. 1, April 2006, pp. 95-104.
Elsevier DOI Texture classification; Irregularly sampled data; Trace transform 0604
BibRef

Kadyrov, A., Talebpour, A., Petrou, M.,
Texture classification with thousands of features,
BMVC02(Poster Session). 0208
BibRef

Brox, T.[Thomas], Weickert, J.[Joachim],
A TV flow based local scale estimate and its application to texture discrimination,
JVCIR(17), No. 5, October 2006, 1053-1073.
Elsevier DOI 0711
BibRef
Earlier:
A TV Flow Based Local Scale Measure for Texture Discrimination,
ECCV04(Vol II: 578-590).
Springer DOI 0405

See also Nonlinear Matrix Diffusion for Optic Flow Estimation. Scale; Texture; Nonlinear diffusion; Segmentation BibRef

Brox, T.[Thomas], Rousson, M.[Mikaël], Deriche, R.[Rachid], Weickert, J.[Joachim],
Unsupervised Segmentation Incorporating Colour, Texture, and Motion,
CAIP03(353-360).
Springer DOI 0311
BibRef
And: INRIARR-4760, Mars 2003.
HTML Version. 0306
BibRef

Rousson, M.[Mikaël], Brox, T.[Thomas], Deriche, R.[Rachid],
Active Unsupervised Texture Segmentation on a Diffusion Based Feature Space,
CVPR03(II: 699-704).
IEEE DOI 0307
BibRef
And: INRIARR-4695, Janvier 2003.
HTML Version. 0306
BibRef

Tzagkarakis, G., Beferull-Lozano, B., Tsakalides, P.,
Rotation-Invariant Texture Retrieval With Gaussianized Steerable Pyramids,
IP(15), No. 9, August 2006, pp. 2702-2718.
IEEE DOI 0608
BibRef

Tzagkarakis, G., Beferull-Lozano, B., Tsakalides, P.,
Rotation-Invariant Texture Retrieval via Signature Alignment Based on Steerable Sub-Gaussian Modeling,
IP(17), No. 7, July 2008, pp. 1212-1225.
IEEE DOI 0806
BibRef

Beferull-Lozano, B., Xie, H.[Hua], Orlegi, A.,
Rotation-invariant features based on steerable transforms with an application to distributed image classification,
ICIP03(III: 521-524).
IEEE DOI 0312
BibRef

Cheng, K.O., Law, N.F., Siu, W.C.,
Multiscale directional filter bank with applications to structured and random texture retrieval,
PR(40), No. 4, April 2007, pp. 1182-1194.
Elsevier DOI 0701
Texture characterization; Texture retrieval; Directional filter bank; Multiscale directional filter bank; Rotation-invariant features BibRef

Mellor, M.[Matthew], Hong, B.W.[Byung-Woo], Brady, M.[Michael],
Locally Rotation, Contrast, and Scale Invariant Descriptors for Texture Analysis,
PAMI(30), No. 1, January 2008, pp. 52-61.
IEEE DOI 0711
New family of filters. BibRef

Wang, M.S.[Ming-Shi], Knoesen, A.[André],
Rotation- and scale-invariant texture features based on spectral moment invariants,
JOSA-A(24), No. 9, September 2007, pp. 2550-2557.
WWW Link. 0801
BibRef

Salzenstein, F.[Fabien], Boudraa, A.O.[Abdel-Ouahab], Cexus, J.C.[Jean-Christophe],
Generalized higher-order nonlinear energy operators,
JOSA-A(24), No. 12, December 2007, pp. 3717-3727.
WWW Link. 0801
BibRef

Zhou, H.[Hui], Wang, R.S.[Run-Sheng], Wang, C.[Cheng],
A novel extended local-binary-pattern operator for texture analysis,
IS(178), No. 22, November, 2008, pp. 4314-4325.
Elsevier DOI 0905
BibRef

Xu, G.L.[Guan-Lei], Wang, X.T.[Xiao-Tong], Xu, X.G.[Xiao-Gang],
Improved bi-dimensional EMD and Hilbert spectrum for the analysis of textures,
PR(42), No. 5, May 2009, pp. 718-734.
Elsevier DOI 0902
Empirical mode decomposition (EMD); Intrinsic mode functions (IMF); Quaternion Hilbert transform; Pseudo extrema BibRef

Xu, G.L.[Guan-Lei], Wang, X.T.[Xiao-Tong], Xu, X.G.[Xiao-Gang],
On analysis of bi-dimensional component decomposition via BEMD,
PR(45), No. 4, 2012, pp. 1617-1626.
Elsevier DOI 1410
Bi-dimensional empirical mode decomposition (BEMD) BibRef

Xu, G.L.[Guan-Lei], Wang, X.T.[Xiao-Tong], Xu, X.G.[Xiao-Gang],
Improved bi-dimensional empirical mode decomposition based on 2d-assisted signals: analysis and application,
IET-IPR(5), No. 3, June 2011, pp. 205-221.
DOI Link 1105
BibRef

Xu, G.L.[Guan-Lei], Wang, X.T.[Xiao-Tong], Zhou, L.J.[Li-Jia], Xu, X.G.[Xiao-Gang],
Image decomposition and texture analysis via combined bi-dimensional Bedrosian's principles,
IET-IPR(12), No. 2, February 2018, pp. 262-273.
DOI Link 1801
BibRef
Earlier: A1, A3, A2, A4:
Assisted signals based mode decomposition,
ICIVC17(868-874)
IEEE DOI 1708
Manganese, Mathematical model, Robustness, assisted signal, bi-dimensional empirical mode decomposition (BEMD), extremum, mode BibRef

Xu, X.G.[Xiao-Gang], Chen, Y.C.[Ying-Cong], Tao, X.[Xin], Jia, J.Y.[Jia-Ya],
Text-Guided Human Image Manipulation via Image-Text Shared Space,
PAMI(44), No. 10, October 2022, pp. 6486-6500.
IEEE DOI 2209
Aerospace electronics, Task analysis, Faces, Training, Natural languages, Image reconstruction, Feature extraction, image and text BibRef

Pu, Y.F., Zhou, J.L., Yuan, X.,
Fractional Differential Mask: A Fractional Differential-Based Approach for Multiscale Texture Enhancement,
IP(19), No. 2, February 2010, pp. 491-511.
IEEE DOI 1002
BibRef

Janney, P.[Pranam], Geers, G.,
Texture classification using invariant features of local textures,
IET-IPR(4), No. 3, June 2010, pp. 158-171.
DOI Link 1006
BibRef

Janney, P.[Pranam], Yu, Z.H.[Zheng-Hua],
Invariant Features of Local Textures: A rotation invariant local texture descriptor,
BP07(1-7).
IEEE DOI 0706
BibRef

Tsai, Y.T.[Yu-Ting], Fang, K.L.[Kuei-Li], Lin, W.C.[Wen-Chieh], Shih, Z.C.[Zen-Chung],
Modeling Bidirectional Texture Functions with Multivariate Spherical Radial Basis Functions,
PAMI(33), No. 7, July 2011, pp. 1356-1369.
IEEE DOI 1106
SRBFs and optimized parameterization. BibRef

Restrepo, A.[Alfredo], Quiroga, J.[Julián],
Root and pre-constant signals of the 1D Teager-Kaiser operator,
SIViP(5), No. 3, September 2011, pp. 363-378.
WWW Link. 1109
BibRef

Quiroga, J.[Julian], Restrepo, A.[Alfredo], Wedefort, L.[Lina], Velasco, M.[Margarita],
On the 2D Teager-Kaiser Operator,
ICIP07(V: 269-272).
IEEE DOI 0709
TK: a discrete, nonlinear moving window filter to compute energy. BibRef

Zhao, Y., Huang, D.S., Jia, W.,
Completed Local Binary Count for Rotation Invariant Texture Classification,
IP(21), No. 10, October 2012, pp. 4492-4497.
IEEE DOI 1209
Local descriptor of texture. BibRef

Zhang, J., Liang, J., Zhao, H.,
Local Energy Pattern for Texture Classification Using Self-Adaptive Quantization Thresholds,
IP(22), No. 1, January 2013, pp. 31-42.
IEEE DOI 1301
BibRef

Tang, L.M.[Li-Ming], He, C.J.[Chuan-Jiang],
Multiscale Texture Extraction with Hierarchical (BV,Gp,L2) Decomposition,
JMIV(45), No. 2, February 2013, pp. 148-163.
WWW Link. 1302
Scale space decomposition BibRef

Sharan, L.[Lavanya], Liu, C.[Ce], Rosenholtz, R.[Ruth], Adelson, E.H.[Edward H.],
Recognizing Materials Using Perceptually Inspired Features,
IJCV(103), No. 3, July 2013, pp. 348-371.
Springer DOI 1306
Plastic, glass, concrete in natural scenes. BibRef

Yang, X.D.[Xiao-Dong], Tian, Y.[Ying_Li],
Texture representations using subspace embeddings,
PRL(34), No. 10, 15 July 2013, pp. 1130-1137.
Elsevier DOI 1306
Texture representation; Texture classification; Subspace embedding. Map texture patches into subspace. BibRef

Hu, R.X.[Rong-Xiang], Jia, W.[Wei], Ling, H.B.[Hai-Bin], Zhao, Y.[Yang], Gui, J.[Jie],
Angular Pattern and Binary Angular Pattern for Shape Retrieval,
IP(23), No. 3, March 2014, pp. 1118-1127.
IEEE DOI 1403
video coding BibRef

Vu, N.S.[Ngoc-Son], Nguyen, T.P.[Thanh Phuong], Garcia, C.[Christophe],
Improving texture categorization with biologically-inspired filtering,
IVC(32), No. 6-7, 2014, pp. 424-436.
Elsevier DOI 1406
Texture classification BibRef

Safia, A.[Abdelmounaime], He, D.C.[Dong-Chen],
Multiband compact texture unit descriptor for intra-band and inter-band texture analysis,
PandRS(105), No. 1, 2015, pp. 169-185.
Elsevier DOI 1506
Texture analysis BibRef

Wang, S.[Sheng], Wu, Q.A.[Qi-Ang], He, X.J.[Xiang-Jian], Yang, J.[Jie], Wang, Y.,
Local N-Ary Pattern and Its Extension for Texture Classification,
CirSysVideo(25), No. 9, September 2015, pp. 1495-1506.
IEEE DOI 1509
BibRef
Earlier: A1, A3, A2, A4, Only:
Generalized local N-ary patterns for texture classification,
AVSS13(324-329)
IEEE DOI 1311
Accuracy. computer vision BibRef

Albukhanajer, W.A., Briffa, J.A., Jin, Y.C.[Yao-Chu],
Evolutionary Multiobjective Image Feature Extraction in the Presence of Noise,
Cyber(45), No. 9, September 2015, pp. 1757-1768.
IEEE DOI 1509
Pareto optimisation BibRef

Wang, Y.[Yu], Zhao, Y.S.[Yong-Sheng], Cai, Q.A.[Qi-Ang], Li, H.S.[Hai-Sheng], Yan, H.X.[Huai-Xin],
A varied local edge pattern descriptor and its application to texture classification,
JVCIR(34), No. 1, 2016, pp. 108-117.
Elsevier DOI 1601
Varied local edge pattern BibRef

Mehta, R.[Rakesh], Egiazarian, K.O.[Karen O.],
Texture Classification Using Dense Micro-Block Difference,
IP(25), No. 4, April 2016, pp. 1604-1616.
IEEE DOI 1604
BibRef
Earlier:
Texture Classification Using Dense Micro-block Difference (DMD),
ACCV14(II: 643-658).
Springer DOI 1504
image classification BibRef

Mehta, R.[Rakesh], Egiazarian, K.O.[Karen O.],
Rotation Invariant Texture Description Using Symmetric Dense Microblock Difference,
SPLetters(23), No. 6, June 2016, pp. 833-837.
IEEE DOI 1606
Encoding BibRef

Rubel, O.[Oleksii], Lukin, V.[Vladimir], Abramov, S.[Sergey], Vozel, B.[Benoit], Egiazarian, K.O.[Karen O.], Pogrebnyak, O.[Oleksiy],
Efficiency of texture image filtering and its prediction,
SIViP(10), No. 8, November 2016, pp. 1543-1550.
Springer DOI 1610
BibRef

Cimpoi, M.[Mircea], Maji, S.[Subhransu], Kokkinos, I.[Iasonas], Vedaldi, A.[Andrea],
Deep Filter Banks for Texture Recognition, Description, and Segmentation,
IJCV(118), No. 1, June 2016, pp. 65-94.
Springer DOI 1605
BibRef
Earlier: A1, A2, A4, Only:
Deep filter banks for texture recognition and segmentation,
CVPR15(3828-3836)
IEEE DOI 1510
BibRef

Lin, T.Y.[Tsung-Yu], Maji, S.[Subhransu],
Visualizing and Understanding Deep Texture Representations,
CVPR16(2791-2799)
IEEE DOI 1612
BibRef

Ahmadvand, A.[Ali], Daliri, M.R.[Mohammad Reza],
Invariant texture classification using a spatial filter bank in multi-resolution analysis,
IVC(45), No. 1, 2016, pp. 1-10.
Elsevier DOI 1601
Texture classification BibRef

Du, H.[Hui], Jin, X.G.[Xiao-Gang], Willis, P.J.[Philip J.],
Two-level joint local laplacian texture filtering,
VC(32), No. 12, December 2016, pp. 1537-1548.
WWW Link. 1611
BibRef

Andrearczyk, V.[Vincent], Whelan, P.F.[Paul F.],
Using filter banks in Convolutional Neural Networks for texture classification,
PRL(84), No. 1, 2016, pp. 63-69.
Elsevier DOI 1612
Texture classification BibRef

Andrearczyk, V.[Vincent], Whelan, P.F.[Paul F.],
Convolutional neural network on three orthogonal planes for dynamic texture classification,
PR(76), No. 1, 2018, pp. 36-49.
Elsevier DOI 1801
Dynamic texture BibRef

Zhao, H.[Hanli], Jiang, L.[Lei], Jin, X.G.[Xiao-Gang], Du, H.[Hui], Li, X.J.[Xu-Jie],
Constant time texture filtering,
VC(34), No. 1, January 2018, pp. 83-92.
WWW Link. 1801
BibRef

Anwer, R.M.[Rao Muhammad], Khan, F.S.[Fahad Shahbaz], van de Weijer, J.[Joost], Molinier, M.[Matthieu], Laaksonen, J.T.[Jorma T.],
Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification,
PandRS(138), 2018, pp. 74-85.
Elsevier DOI 1804
Remote sensing, Deep learning, Scene classification, Local Binary Patterns, Texture analysis BibRef

Xu, P.P.[Pan-Pan], Wang, W.C.[Wen-Cheng],
Improved Bilateral Texture Filtering With Edge-Aware Measurement,
IP(27), No. 7, July 2018, pp. 3621-3630.
IEEE DOI 1805
Frequency measurement, Image edge detection, Noise measurement, Shape, Smoothing methods, Visualization, image texture analysis BibRef

Song, T.C.[Tie-Cheng], Li, H.L.[Hong-Liang], Meng, F.M.[Fan-Man], Wu, Q.B.[Qing-Bo], Cai, J.F.[Jian-Fei],
LETRIST: Locally Encoded Transform Feature Histogram for Rotation-Invariant Texture Classification,
CirSysVideo(28), No. 7, July 2018, pp. 1565-1579.
IEEE DOI 1807
Locally Encoded TRansform feature hISTogram. Computational modeling, Feature extraction, Histograms, Lighting, Quantization (signal), Robustness, Transforms, texture analysis BibRef

Ding, Y.Y.[Yan-Yun], Xiao, Y.H.[Yun-Hai],
Symmetric Gauss-Seidel Technique-Based Alternating Direction Methods of Multipliers for Transform Invariant Low-Rank Textures Problem,
JMIV(60), No. 8, October 2018, pp. 1220-1230.
Springer DOI 1810
Transform invariant low-rank textures: TILT. BibRef

Liu, L.[Li], Chen, J.[Jie], Zhao, G.Y.[Guo-Ying], Fieguth, P.W.[Paul W.], Chen, X.L.[Xi-Lin], Pietikäinen, M.[Matti],
Texture Classification in Extreme Scale Variations Using GANet,
IP(28), No. 8, August 2019, pp. 3910-3922.
IEEE DOI 1907
convolutional neural nets, genetic algorithms, image classification, image coding, image filtering, image texture, texture analysis BibRef

Xu, P., Wang, W.,
Structure-Aware Window Optimization for Texture Filtering,
IP(28), No. 9, Sep. 2019, pp. 4354-4363.
IEEE DOI 1908
adaptive filters, image filtering, image texture, optimisation, structure-aware window optimization, texture filtering, image texture analysis BibRef

Mihoubi, S.[Sofiane], Losson, O.[Olivier], Mathon, B.[Benjamin], Macaire, L.[Ludovic],
Spatio-spectral binary patterns based on multispectral filter arrays for texture classification,
JOSA-A(35), No. 9, September 2018, pp. 1532-1542.
DOI Link 1912
Image processing, Multispectral and hyperspectral imaging, Color imaging, Image stacking, Light wavelength, Spectral discrimination BibRef

Hu, Y.T.[Yu-Ting], Wang, Z.[Zhen], Al Regib, G.[Ghassan],
Texture classification using block intensity and gradient difference (BIGD) descriptor,
SP:IC(83), 2020, pp. 115770.
Elsevier DOI 2003
Local descriptor, Block intensity and gradient difference (), Local feature extraction, Multi-scale, Texture classification BibRef

Mohammadi, S.[Sina], Noori, M.[Mehrdad], Bahri, A.[Ali], Ribas, L.C.[Lucas C.], de Mesquita Sá Junior, J.J.[Jarbas Joaci], Scabini, L.F.S.[Leonardo F.S.], Bruno, O.M.[Odemir M.],
Fusion of complex networks and randomized neural networks for texture analysis,
PR(103), 2020, pp. 107189.
Elsevier DOI 2005
Randomized neural networks, Complex networks, Texture analysis, Feature extraction BibRef

Scabini, L.F.S.[Leonardo F.S.], Zielinski, K.M.[Kallil M.], Ribas, L.C.[Lucas C.], Gonçalves, W.N.[Wesley N.], de Baets, B.[Bernard], Bruno, O.M.[Odemir M.],
RADAM: Texture recognition through randomized aggregated encoding of deep activation maps,
PR(143), 2023, pp. 109802.
Elsevier DOI 2310
Texture analysis, Randomized neural networks, Transfer learning, Convolutional networks, Feature extraction BibRef

Zielinski, K.M.C.[Kallil M. C.], Ribas, L.C.[Lucas C.], Scabini, L.F.S.[Leonardo F. S.], Bruno, O.M.[Odemir M.],
Complex Texture Features Learned by Applying Randomized Neural Network on Graphs,
IPTA22(1-6)
IEEE DOI 2206
Visualization, Recurrent neural networks, Image recognition, Databases, Plants (biology), Complex networks, Feature extraction, Pattern Recognition BibRef

Farfán, A.J.F.[Alex J. F.], Scabini, L.F.S.[Leonardo F. S.], Bruno, O.M.[Odemir M.],
A Web-Based System to Assess Texture Analysis Methods and Datasets,
CAIP19(II:425-437).
Springer DOI 1909
BibRef

Scabini, L.F.S.[Leonardo F. S.], Condori, R.H.M.[Rayner H. M.], Ribas, L.C.[Lucas C.], Bruno, O.M.[Odemir M.],
Evaluating Deep Convolutional Neural Networks as Texture Feature Extractors,
CIAP19(II:192-202).
Springer DOI 1909
BibRef

Bohra, M.[Murtuza], Maheshwari, S.[Sajal], Gandhi, V.[Vineet],
TextureToMTF: predicting spatial frequency response in the wild,
SIViP(14), No. 6, September 2020, pp. 1163-1170.
WWW Link. 2008
BibRef

Dong, X., Zhou, H., Dong, J.,
Texture Classification Using Pair-Wise Difference Pooling-Based Bilinear Convolutional Neural Networks,
IP(29), 2020, pp. 8776-8790.
IEEE DOI 2009
Feature extraction, Visualization, Convolutional neural networks, Principal component analysis, Machine learning, BCNNs BibRef

El Khadiri, I.[Issam], El Merabet, Y.[Youssef], Tarawneh, A.S.[Ahmad S.], Ruichek, Y.[Yassine], Chetverikov, D.[Dmitry], Touahni, R.[Raja], Hassanat, A.B.[Ahmad B.],
Petersen Graph Multi-Orientation Based Multi-Scale Ternary Pattern (PGMO-MSTP): An Efficient Descriptor for Texture and Material Recognition,
IP(30), 2021, pp. 4571-4586.
IEEE DOI 2105
Feature extraction, Image coding, Gray-scale, Real-time systems, Histograms, LGS, LTP, wilcoxon signed rank test BibRef

Amziane, A.[Anis], Losson, O.[Olivier], Mathon, B.[Benjamin], Macaire, L.[Ludovic],
MSFA-Net: A convolutional neural network based on multispectral filter arrays for texture feature extraction,
PRL(168), 2023, pp. 93-99.
Elsevier DOI 2304
Multispectral imaging, Texture feature extraction, Multispectral filter array, Supervised classification, Precision farming BibRef


Shih, H., Cheng, H., Fu, J.,
An Improved Local Ternary Pattern for Texture Classification,
ICIP19(4415-4418)
IEEE DOI 1910
Local ternary pattern, rotation invariance, scale invariance, texture classification, texture representation BibRef

Pham, M.T.[Minh-Tan],
Efficient Texture Retrieval Using Multiscale Local Extrema Descriptors and Covariance Embedding,
CEFR-LCV18(IV:564-579).
Springer DOI 1905
BibRef

Zhang, H.[Hang], Xue, J.[Jia], Dana, K.J.[Kristin J.], Zhang, H., Xue, J., Dana, K.,
Deep TEN: Texture Encoding Network,
CVPR17(2896-2905)
IEEE DOI 1711
Convolutional codes, Dictionaries, Encoding, Feature extraction, Machine learning, Pipelines, Visualization BibRef

Marcos, D., Volpi, M., Tuia, D.,
Learning rotation invariant convolutional filters for texture classification,
ICPR16(2012-2017)
IEEE DOI 1705
Convolutional codes, Feature extraction, Interpolation, Lighting, Neural networks, Standards, Training BibRef

Brandtberg, T.,
Virtual hexagonal and multi-scale operator for fuzzy rank order texture classification using one-dimensional generalised Fourier analysis,
ICPR16(2018-2024)
IEEE DOI 1705
Feature extraction, Fourier transforms, Geometry, Image edge detection, Lighting, Shape BibRef

Shahriari, A.[Arash],
Learning of Separable Filters by Stacked Fisher Convolutional Autoencoders,
BMVC16(xx-yy).
HTML Version. 1805
BibRef
And:
Parametric Learning of Texture Filters by Stacked Fisher Autoencoders,
DICTA16(1-8)
IEEE DOI 1701
Convolutional codes BibRef

Vieira, R.T.[Raissa Tavares], Negri, T.T.[Tamiris Trevisan], Gonzaga, A.[Adilson],
Robustness of Rotation Invariant Descriptors for Texture Classification,
ISVC16(I: 268-277).
Springer DOI 1701
BibRef

Shahriari, A.,
Learning deep filter banks in parallel for texture recognition,
ICIP16(1634-1638)
IEEE DOI 1610
Feature extraction BibRef

Hu, Y., Long, Z., Al Regib, G.,
Completed local derivative pattern for rotation invariant texture classification,
ICIP16(3548-3552)
IEEE DOI 1610
Databases BibRef

Yang, H.[Hang], Zhu, M.[Ming], Niu, Y.[Yan], Guan, Y.J.[Yu-Jing], Zhang, Z.B.[Zhong-Bo],
Dual domain filters based texture and structure preserving image non-blind deconvolution,
CVPR15(705-713)
IEEE DOI 1510
BibRef

Polisano, K.[Kevin], Clausel, M.[Marianne], Perrier, V.[Valerie], Condat, L.[Laurent],
Texture modeling by Gaussian fields with prescribed local orientation,
ICIP14(6091-6095)
IEEE DOI 1502
Biological system modeling BibRef

Gonzalez-Castro, V.[Victor], Debayle, J.[Johan], Curie, V.[Vladimir],
Pixel Classification Using General Adaptive Neighborhood-Based Features,
ICPR14(3750-3755)
IEEE DOI 1412
Accuracy General Adaptive Neighborhoods for texture. BibRef

Mohammed, N.[Nabeel], Squire, D.M.[David McG.],
ICFSIFT: Improving Collection-Specific CBIR with ICF-Based Local Features,
DICTA13(1-8)
IEEE DOI 1402
BibRef
Earlier:
Efficient and accurate independent component filter-based features for texure similarity,
ICIP13(2887-2891)
IEEE DOI 1402
content-based retrieval BibRef

Hill, P.R., Achim, A., Bull, D.R., Al-Mualla, M.E.,
Image Denoising Using Dual Tree Statistical Models for Complex Wavelet Transform Coefficient Magnitudes,
ICIP13(88-92)
IEEE DOI 1402
Equations
See also Rotationally Invariant Texture Based Features. BibRef

Said, S.[Salem], Bombrun, L.[Lionel], Berthoumieu, Y.[Yannick],
Texture classification using Rao's distance: An EM algorithm on the Poincare half plane,
ICIP15(3466-3470)
IEEE DOI 1512
EM algorithm BibRef

Bombrun, L.[Lionel], Berthoumieu, Y.[Yannick],
Multivariate texture retrieval using the Kullback-Leibler divergence between bivariate generalized Gamma times an Uniform distribution,
ICIP12(2413-2416).
IEEE DOI 1302
BibRef

Guerreiro, R.F.C.[Rui F. C.], Aguiar, P.M.Q.[Pedro M. Q.],
Learning simple texture discrimination filters,
ICIP10(261-264).
IEEE DOI 1009
BibRef

Nguyen, H.G.[Huu-Giao], Fablet, R.[Ronan], Boucher, J.M.[Jean-Marc],
Multivariate log-Gaussian Cox models of elementary shapes for recognizing natural scene categories,
ICIP11(665-668).
IEEE DOI 1201
BibRef
And:
Visual textures as realizations of multivariate log-Gaussian Cox processes,
CVPR11(2945-2952).
IEEE DOI 1106
BibRef
Earlier:
Spatial Statistics of Visual Keypoints for Texture Recognition,
ECCV10(IV: 764-777).
Springer DOI 1009
BibRef

Dollar, P.[Piotr], Tu, Z.W.[Zhuo-Wen], Perona, P.[Pietro], Belongie, S.J.[Serge J.],
Integral Channel Features,
BMVC09(xx-yy).
PDF File. 0909
Multiple features computed from linear and non-linear operators. Not just for textures. BibRef

Kondra, S.[Shripad], Torre, V.[Vincent],
Texture Classification Using Three Circular Filters,
ICCVGIP08(429-434).
IEEE DOI 0812
BibRef

Bors, A.G.[Adrian G.], Nasios, N.[Nikolaos],
Kernel bandwidth estimation in methods based on probability density function modelling,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Ray, N.[Nilanjan], Saha, B.[Baidyanath], Acton, S.T.[Scott T.],
Oil sand image segmentation using the inclusion filter,
ICIP08(2188-2191).
IEEE DOI 0810
BibRef

Ray, N., Acton, S.T.,
Self-dual inclusion filters for grayscale imagery,
ICIP03(I: 321-324).
IEEE DOI 0312
BibRef

Daurat, A.[Alain], Tajine, M.[Mohamed], Zouaoui, M.[Mahdi],
About the Frequencies of Some Patterns in Digital Planes: Application to Area Estimators,
DGCI08(xx-yy).
Springer DOI 0804
BibRef

Muñiz, R.[Rubén], Corrales, J.A.[José Antonio],
An Approach for Extracting Illumination-Independent Texture Features,
ICIAR07(93-104).
Springer DOI 0708
BibRef

Muñiz, R.[Rubén], Corrales, J.A.[José Antonio], Rico-Secades, M.[Manuel],
Use of band ratioing for building illumination independent texture classification systems,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Chamorro-Martínez, J., Martínez-Jiménez, P.,
Texture Measuring by Means of Perceptually-Based Fineness Functions,
IbPRIA09(265-272).
Springer DOI 0906
BibRef
And:
A comparative study of texture coarseness measures,
ICIP09(1337-1340).
IEEE DOI 0911
BibRef

Chamorro-Martínez, J., Galán-Perales, E., Prados-Suárez, B., Soto-Hidalgo, J.M.,
Perceptually-Based Functions for Coarseness Textural Feature Representation,
IbPRIA07(I: 579-586).
Springer DOI 0706
BibRef

Vidal-Naquet, M.[Michel], Tanifuji, M.[Manabu],
The effective resolution of correlation filters applied to natural scenes,
BP07(1-6).
IEEE DOI 0706
BibRef

Hussain, A., Rajpoot, N., Rajpoot, K.,
Texture Classification with Ants,
ICIP06(3013-3016).
IEEE DOI 0610
BibRef

Verzakov, S., Paclík, P., Duin, R.P.W.,
The Tangent Kernel Approach to Illumination-Robust Texture Classification,
SCIA05(1009-1016).
Springer DOI 0506
BibRef

Silva Santos, C., Kogler, J.E., del Moral Hernandez, E.,
Using Independent Subspace Analysis for Selecting Filters Used in Texture Processing,
ICIP05(I: 465-468).
IEEE DOI 0512
BibRef

van de Wouwer, G., Weyn, B., van Dyck, D.,
Multiscale, asymmetry signatures for texture analysis,
ICIP04(III: 1517-1520).
IEEE DOI 0505
BibRef

Sabri, M., Alirezaie, J.,
Optimized space frequency kernel for texture classification,
ICIP04(III: 1521-1524).
IEEE DOI 0505
BibRef

Costantini, R., Menegaz, G., Susstrunk, S.,
A measure for spatial dependence in natural stochastic textures,
ICIP04(III: 1525-1528).
IEEE DOI 0505
BibRef

Koroutchev, K.[Kostadin], Dorronsoro, J.R.[José R.],
Factorization of Natural 4X4 Patch Distributions,
SMVP04(165-174).
Springer DOI 0505
BibRef

Cuenca, S.A.,
Texture analysis based on local semicovers,
CIAP03(588-593).
IEEE DOI 0310
BibRef

Liu, X.W.[Xiu-Wen], Cheng, L.[Lei],
Independent filters for texture classification,
ICIP02(III: 113-116).
IEEE DOI 0210
BibRef

Schael, M.,
Invariant Texture Classification Using Group Averaging with Relational Kernel Functions,
Texture02(129-134). 0207
BibRef

Clark, A.A.,
Texture Deconvolution for the Fourier-Based Analysis of Non-Rectangular Regions,
BMVC99(Posters/Demos).
PDF File. BibRef 9900

Heikkinen, K., Vuorimaa, P.,
Computation of two texture features in hardware,
CIAP99(125-129).
IEEE DOI 9909
BibRef

Huet, F., Mattioli, J.,
A textural analysis by mathematical morphology transformations: structural opening and top-hat,
ICIP96(III: 49-52).
IEEE DOI 9610
BibRef

Jackson, S., Ahuja, N.,
Elliptical Gaussian Filters,
ICPR96(II: 775-779).
IEEE DOI 9608
(Intel Corporation, USA) BibRef

Ma, W.Y., Manjunath, B.S.,
A Comparison of Wavelet Features for Texture Annotation,
ICIP95(II: 256-259).
IEEE DOI
PDF File. 9510
BibRef

Greenhill, D., Davies, E.R.,
Texture Analysis Using Neural Networks and Mode Filters,
BMVC93(xx-yy).
PDF File. 9309
BibRef

Lonnestad, T.,
A new set of texture features based on the Haar transform,
ICPR92(III:676-679).
IEEE DOI 9208
BibRef

Lee, H.Y.,
Extraction of Textured Regions in Aerial Imagery,
DARPA83(298-303). BibRef 8300

Laws, K.I.[Kenneth I.],
Rapid Texture Identification,
SPIEConf. Image Processing for Missile Guidance, 1980, pp. 376-380. BibRef 8000

Laws, K.I.[Kenneth I.],
Texture Energy Measures,
DARPAN79(47-51). BibRef 7900 USC Computer VisionIntroduces the texture measures developed in his thesis.
See also Textured Image Segmentation. BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Local Binary Patterns, LPB for Texture .


Last update:Mar 16, 2024 at 20:36:19