*Result*: Texture Image Classification Using Effective Texture Descriptors.
Title:
Texture Image Classification Using Effective Texture Descriptors.
Authors:
Gopalakrishnan K; Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India., Karthikeyan V; Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India., Harshini P; Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India., Ramasabitha N; Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India.
Source:
Journal of texture studies [J Texture Stud] 2025 Oct; Vol. 56 (5), pp. e70049.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Wiley Country of Publication: England NLM ID: 0252052 Publication Model: Print Cited Medium: Internet ISSN: 1745-4603 (Electronic) Linking ISSN: 00224901 NLM ISO Abbreviation: J Texture Stud Subsets: MEDLINE
Imprint Name(s):
Publication: 2005- : Oxford : Wiley
Original Publication: Dordrecht, Reidel.
Original Publication: Dordrecht, Reidel.
MeSH Terms:
References:
Abusham, E. E., and H. K. Bashir. 2011. “Face Recognition Using Local Graph Structure (LGS).” In International Conference on Human‐Computer Interaction, 169–175. Springer.
Bashier, H. K., L. S. Hoe, L. T. Hui, et al. 2016. “Texture Classification via Extended Local Graph Structure.” Optik 127, no. 2: 638–643.
Beliakov, G., S. James, and L. Troiano. 2008. “Texture Recognition by Using GLCM and Various Aggregation Functions.” In 2008 IEEE International Conference on Fuzzy Systems (FUZZ 2008), 1280–1284. IEEE.
Chen, J., S. Shan, C. He, et al. 2009. “WLD: A Robust Local Image Descriptor.” IEEE Transactions on Pattern Analysis and Machine Intelligence 32, no. 9: 1705–1720.
Chen, L.‐C., G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. 2017. “DeepLab: Semantic Image Segmentation With Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40, no. 4: 834–848.
Chen, Z., Y. Quan, R. Xu, L. Jin, and Y. Xu. 2024. “Enhancing Texture Representation With Deep Tracing Pattern Encoding.” Pattern Recognition 146: 109959.
Choy, S. K., and C. S. Tong. 2008. “Statistical Properties of Bit‐Plane Probability Model and Its Application in Supervised Texture Classification.” IEEE Transactions on Image Processing 17, no. 8: 1399–1405.
Chu, J., Z. Guo, and L. Leng. 2018. “Object Detection Based on Multi‐Layer Convolution Feature Fusion and Online Hard Example Mining.” IEEE Access 6: 19959–19967.
Dong, Y., J. Feng, L. Liang, L. Zheng, and Q. Wu. 2017. “Multiscale Sampling‐Based Texture Image Classification.” IEEE Signal Processing Letters 24, no. 5: 614–618.
Dong, Y., J. Feng, C. Yang, X. Wang, L. Zheng, and J. Pu. 2018. “Multi‐Scale Counting and Difference Representation for Texture Classification.” Visual Computer 34, no. 10: 1315–1324.
Dong, Y., and J. Ma. 2011. “Contourlet‐Based Texture Classification With Product Bernoulli Distributions.” In Advances in Neural Networks—ISNN, vol. 6676, 9–18. Springer.
Dong, Y., and J. Ma. 2012. “Texture Classification Based on Contourlet Sub Band Clustering.” In Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence, 421–426. Springer.
Dong, Y., and J. Ma. 2018. “Multiscale Counting and Difference Representation for Texture Classification.” Visual Computer 34, no. 10: 1315–1324.
Dong, Y., T. Wang, C. Yang, et al. 2019. “Locally Directional and Extremal Pattern for Texture Classification.” IEEE Access 7: 87931–87942.
Dong, Y., H. Wu, X. Li, C. Zhou, and Q. Wu. 2018. Multiscale Symmetric Dense Micro‐Block Difference for Texture Classification. IEEE Transactions on Circuits and Systems for Video Technology. https://doi.org/10.1109/TCSVT.2018.2883825.
Du, C., and S. Gao. 2017. “Image Segmentation‐Based Multi‐Focus Image Fusion Through Multi‐Scale Convolutional Neural Network.” IEEE Access 5: 15750–15761.
El Merabet, Y., Y. Ruichek, and A. El Idrissi. 2019. “Attractive‐and‐Repulsive Center‐Symmetric Local Binary Patterns for Texture Classification.” Engineering Applications of Artificial Intelligence 78: 158–172.
Fernández, A., M. X. Álvarez, and F. Bianconi. 2013. “Texture Description Through Histograms of Equivalent Patterns.” Journal of Mathematical Imaging and Vision 45, no. 1: 76–102.
Górriz, J. M., J. Ramírez, J. Suckling, et al. 2017. “Case‐Based Statistical Learning: A Non‐Parametric Implementation With a Conditional‐Error Rate SVM.” IEEE Access 5: 11468–11478.
Guo, X., Y. Li, and H. Ling. 2017. “LIME: Low‐Light Image Enhancement via Illumination Map Estimation.” IEEE Transactions on Image Processing 26, no. 2: 982–993.
Guo, Z., L. Zhang, and D. Zhang. 2010. “A Completed Modeling of Local Binary Pattern Operator for Texture Classification.” IEEE Transactions on Image Processing 19, no. 6: 1657–1663.
Hassner, T., S. Filosof, V. Mayzels, and L. Zelnik‐Manor. 2017. “Sifting Through Scales.” IEEE Transactions on Pattern Analysis and Machine Intelligence 39, no. 7: 1431–1443.
Hazgui, M., H. Ghazouani, and W. Barhoumi. 2022. “Genetic Programming‐Based Fusion of HOG and LBP Features for Fully Automated Texture Classification.” Visual Computer 38, no. 2: 457–476.
He, K., X. Zhang, S. Ren, and J. Sun. 2016. “Deep Residual Learning for Image Recognition.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 770–778. IEEE Explore.
Hong, X., G. Zhao, M. Pietikäinen, and X. Chen. 2014. “Combining LBP Difference and Feature Correlation for Texture Description.” IEEE Transactions on Image Processing 23, no. 6: 2557–2568.
Hu, S., J. Li, H. Fan, S. Lan, and Z. Pan. 2024. “Scale and Pattern Adaptive Local Binary Pattern for Texture Classification.” Expert Systems With Applications 240: 122403.
Ji, L., Y. Ren, G. Liu, and X. Pu. 2017. “Training‐Based Gradient LBP Feature Models for Multiresolution Texture Classification.” IEEE Transactions on Cybernetics 48, no. 9: 2683–2696.
Jiang, N., J. Xu, W. Yu, and S. Goto. 2013. “Gradient Local Binary Patterns for Human Detection.” In In 2013 IEEE International Symposium on Circuits and Systems (ISCAS), 978–981. IEEE.
Kannala, J., and E. Rahtu. 2012. “Bsif: Binarized Statistical Image Features.” In Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), 1363–1366. IEEE.
Karthikeyan, V., and S. S. Priyadharsini. 2024. “Text‐Independent Voiceprint Recognition via Compact Embedding of Dilated Deep Convolutional Neural Networks.” Computers and Electrical Engineering 118: 109408.
Karthikeyan, V., E. Raja, and K. Gurumoorthy. 2024. “Denoising Convolutional Neural Network With Energy‐Based Attention for Image Enhancement.” Journal of Applied Analysis and Computation 14, no. 4: 1893–1914.
Karthikeyan, V., and S. Suja Priyadharsini. 2024. “A Stacked Convolutional Neural Network Framework With Multi‐Scale Attention Mechanism for Text‐Independent Voiceprint Recognition.” Pattern Analysis and Applications 27, no. 2: 1–15.
Khadiri, E., I, Y. E. Merabet, A. S. Tarawneh, Y. Ruichek, D. Chetverikov, and R. Touahni. 2021. “Petersen Graph Multi‐Orientation Based Multi‐Scale Ternary Pattern (PGMO‐MSTP): An Efficient Descriptor for Texture and Material Recognition.” In IEEE Transactions on Image Processing, vol. 30, 4571–4586. IEEE. https://doi.org/10.1109/TIP.2021.3070188.
Khadiri, I. E., A. Chahi, Y. E. Merabet, Y. Ruichek, and R. Touahni. 2018. “Local Directional Ternary Pattern: A New Texture Descriptor for Texture Classification.” Computer Vision and Image Understanding 169: 14–27.
Khadiri, I. E., M. Kas, Y. El Merabet, Y. Ruichek, and R. Touahni. 2018. “Repulsive‐and‐Attractive Local Binary Gradient Contours: New and Efficient Feature Descriptors for Texture Classification.” Information Sciences 467: 634–653.
Khan, F. S., R. M. Anwer, J. Van De Weijer, M. Felsberg, and J. Laaksonen. 2015. “Compact Color–Texture Description for Texture Classification.” Pattern Recognition Letters 51: 16–22.
Lan, S., J. Li, S. Hu, H. Fan, and Z. Pan. 2024. “A Neighbourhood Feature‐Based Local Binary Pattern for Texture Classification.” Visual Computer 40, no. 5: 3385–3409.
Lategahn, H., S. Gross, T. Stsehle, and T. Aach. 2010. “Texture Classification by Modelling Joint Distributions of Local Patterns With Gaussian Mixtures.” IEEE Transactions on Image Processing 19, no. 6: 1548–1557.
Lehmann, F. 2011. “Turbo Segmentation of Textured Images.” IEEE Transactions on Pattern Analysis and Machine Intelligence 33, no. 1: 16–29.
Liu, L., P. Fieguth, G. Kuang, and H. Zha. 2011. “Sorted Random Projections for Robust Texture Classification.” In 2011 International Conference on Computer Vision, 391–398. IEEE.
Liu, L., S. Lao, P. W. Fieguth, Y. Guo, X. Wang, and M. Pietikäinen. 2016. “Median Robust Extended Local Binary Pattern for Texture Classification.” IEEE Transactions on Image Processing 25, no. 3: 1368–1381.
Lu, Y., and D. Song. 2015. “Visual Navigation Using Heterogeneous Landmarks and Unsupervised Geometric Constraints.” IEEE Transactions on Robotics 31, no. 3: 736–749.
Mohanaiah, P., P. Sathyanarayana, and L. GuruKumar. 2013. “Image Texture Feature Extraction Using GLCM Approach.” International Journal of Scientific and Research Publications 3, no. 5: 1–5.
Nanni, L., S. Brahnam, and A. Lumini. 2012. “A Simple Method for Improving Local Binary Patterns by Considering Nonuniform Patterns.” Pattern Recognition 45, no. 10: 3844–3852.
Ojala, T., M. Pietikäinen, and D. Harwood. 1996. “A Comparative Study of Texture Measures With Classification Based on Featured Distributions.” Pattern Recognition 29, no. 1: 51–59.
Ojala, T., M. Pietikäinen, and T. Mäenpää. 2002. “Multiresolution Gray‐Scale and Rotation Invariant Texture Classification With Local Binary Patterns.” IEEE Transactions on Pattern Analysis and Machine Intelligence 24, no. 7: 971–987.
Ouslimani, F., A. Ouslimani, and Z. Ameur. 2025. “Robust Directional Median Pattern for Noisy Texture Classification.” Multimedia Tools and Applications 84, no. 1: 131–145.
Pillai, A., R. Soundrapandiyan, S. Satapathy, S. C. Satapathy, K. H. Jung, and R. Krishnan. 2018. “Local Diagonal Extrema Number Pattern: A New Feature Descriptor for Face Recognition.” Future Generation Computer Systems 81: 297–306.
Rainer, G., A. Ghosh, W. Jakob, and T. Weyrich. 2020. “Unified Neural Encoding of BTFs.” Computer Graphics Forum 39, no. 2: 167–178.
Ren, J., X. Jiang, and J. Yuan. 2013. “Noise‐Resistant Local Binary Pattern With an Embedded Error‐Correction Mechanism.” IEEE Transactions on Image Processing 22, no. 10: 4049–4060.
Rezaei, M., M. Saberi, and S. F. Ershad. 2011. “Texture Classification Approach Based on Combination of Random Threshold Vector Technique and Co‐Occurrence Matrixes.” In Proceedings of 2011 International Conference on Computer Science and Network Technology, vol. 4, 2303–2306. IEEE.
Saniei, T., M. Kianersi, and S. Fekri‐Ershad. 2024. “Assessing Relations Among Visual Variables in Hotel Lobbies Using Deep Learning.” Interiority 7, no. 2: 175–198.
Satpathy, A., X. Jiang, and H. L. Eng. 2014. “LBP‐Based Edge‐Texture Features for Object Recognition.” IEEE Transactions on Image Processing 23, no. 5: 1953–1964.
Shao, J., C. C. Loy, and X. Wang. 2017. “Learning Scene‐Independent Group Descriptors for Crowd Understanding.” IEEE Transactions on Circuits and Systems for Video Technology 27, no. 6: 1290–1303.
Sima, J., Y. Dong, T. Wang, L. Zheng, and J. Pu. 2018. “Extended Contrast Local Binary Pattern for Texture Classification.” International Journal of New Technology and Research 4, no. 3: 263120.
Su, H., J. Chen, Z. Li, H. Meng, and X. Wang. 2024. “The Fusion Feature Wavelet Pyramid Based on FCIS and GLCM for Texture Classification.” International Journal of Machine Learning and Cybernetics 15, no. 5: 1907–1926.
Su, H., and C. Jung. 2018. “Perceptual Enhancement of Low Light Images Based on Two‐Step Noise Suppression.” IEEE Access 6: 7005–7018.
Subrahmanyam, M., R. P. Maheshwari, and R. Balasubramanian. 2012. “Local Maximum Edge Binary Patterns: A New Descriptor for Image Retrieval and Object Tracking.” Signal Processing 92, no. 6: 1467–1479.
Sun, X., J. Wang, M. F. She, and L. Kong. 2013. “Scale Invariant Texture Classification via Sparse Representation.” Neurocomputing 122: 338–348.
Szegedy, C., W. Liu, Y. Jia, et al. 2015. “Going Deeper With Convolutions.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1–9. IEEE Explore.
Tan, X., and B. Triggs. 2010. “Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions.” IEEE Transactions on Image Processing 19, no. 6: 1635–1650.
Tang, K., S. Peng, and X. Chen. 2017. “3D Object Recognition in Cluttered Scenes With Robust Shape Description and Correspondence Selection.” IEEE Access 5: 1833–1845.
Teixeira, L. O., D. Bertolini, L. S. Oliveira, G. D. Cavalcanti, and Y. M. Costa. 2025. “Triplet Dissimilarity: A Texture Classification Approach Using Dissimilarity and Siamese Networks.” Soft Computing 29, no. 11–12: 1–18.
Tiwari, S., A. K. Sharma, I. Abdul Aziz, et al. 2025. “Investigations on Segmentation‐Based Fractal Texture for Texture Classification in the Presence of Gaussian Noise.” PLoS One 20, no. 1: e0315135.
Tuncer, T., S. Dogan, and F. Ertam. 2019. “A Novel Neural Network Based Image Descriptor for Texture Classification.” Physica A: Statistical Mechanics and Its Applications 526: 120955.
Vácha, P., and M. Haindl. 2011. “Texture Recognition Using Robust Markovian Features.” In Internatinoal Workshop on Computational Intelligence for Multimedia Understanding, 126–137. Springer.
Varma, M., and A. Zisserman. 2005. “A Statistical Approach to Texture Classification From Single Images.” International Journal of Computer Vision 62, no. 1: 61–81.
Varun Prakash, R., V. Karthikeyan, S. Vishali, and M. Karthika. 2024. “Multi‐Level LSTM Framework With Hybrid Sonic Features for Human–Animal Conflict Evasion.” Visual Computer 41: 1–17.
Velayuthapandian, K., N. Murugan, and S. Paramasivan. 2024. “End‐to‐End CNN Conceptual Model for a Biometric Authentication Mechanism for ATM Machines.” Discover Electronics 1, no. 1: 26.
Velayuthapandian, K., M. Veyilraj, and M. A. Jayakumaraj. 2024. “An Intelligent Parking Allocation Framework for Digital Society 5.0.” Intelligent Decision Technologies 18, no. 3: 2145–2159.
Wang, W., J. Shen, R. Yang, and F. Porikli. 2018. “Saliency‐Aware Video Object Segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40, no. 1: 20–33.
Wang, Y., Y. Shao, Y. Quan, and Y. Liu. 2017. “Noise Removal of Low‐Dose CT Images Using Modified Smooth Patch Ordering.” IEEE Access 5: 26092–26103.
Xie, J., L. Zhang, J. You, and S. Shiu. 2015. “Effective Texture Classification by Texton Encoding Induced Statistical Features.” Pattern Recognition 48, no. 2: 447–457.
Xu, X., and B. Li. 2025. “Multi Scale Supervised Entropy Weighted Binary Pattern for Texture Classification.” Scientific Reports 15, no. 1: 26087.
Yavuz, B. C., N. Yurtay, and O. Ozkan. 2018. “Prediction of Protein Secondary Structure With Clonal Selection Algorithm and Multilayer Perceptron.” IEEE Access 6: 45256–45261.
Yuan, Y., L. Mou, and X. Lu. 2015. “Scene Recognition by Manifold Regularized Deep Learning Architecture.” IEEE Transactions on Neural Networks and Learning Systems 26, no. 10: 2222–2233.
Zhang, J., H. Zhao, and J. Liang. 2013. “Continuous Rotation Invariant Local Descriptors for Texton Dictionary‐Based Texture Classification.” Computer Vision and Image Understanding 117, no. 1: 56–75.
Zhang, L., Z. Zhou, and H. Li. 2012. “Binary Gabor Pattern: An Efficient and Robust Descriptor for Texture Classification.” In 2012 19th IEEE International Conference on Image Processing, 81–84. IEEE.
Zhang, T., S. Liu, C. Xu, B. Liu, and M.‐H. Yang. 2018. “Correlation Particle Filter for Visual Tracking.” IEEE Transactions on Image Processing 27, no. 6: 2676–2687.
Zhao, Y., D.‐S. Huang, and W. Jia. 2012. “Completed Local Binary Count for Rotation Invariant Texture Classification.” IEEE Transactions on Image Processing 21, no. 10: 4492–4497.
Zhu, H., K.‐V. Yuen, L. Mihaylova, and H. Leung. 2017. “Overview of Environment Perception for Intelligent Vehicles.” IEEE Transactions on Intelligent Transportation Systems 18, no. 10: 2584–2601.
Bashier, H. K., L. S. Hoe, L. T. Hui, et al. 2016. “Texture Classification via Extended Local Graph Structure.” Optik 127, no. 2: 638–643.
Beliakov, G., S. James, and L. Troiano. 2008. “Texture Recognition by Using GLCM and Various Aggregation Functions.” In 2008 IEEE International Conference on Fuzzy Systems (FUZZ 2008), 1280–1284. IEEE.
Chen, J., S. Shan, C. He, et al. 2009. “WLD: A Robust Local Image Descriptor.” IEEE Transactions on Pattern Analysis and Machine Intelligence 32, no. 9: 1705–1720.
Chen, L.‐C., G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. 2017. “DeepLab: Semantic Image Segmentation With Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40, no. 4: 834–848.
Chen, Z., Y. Quan, R. Xu, L. Jin, and Y. Xu. 2024. “Enhancing Texture Representation With Deep Tracing Pattern Encoding.” Pattern Recognition 146: 109959.
Choy, S. K., and C. S. Tong. 2008. “Statistical Properties of Bit‐Plane Probability Model and Its Application in Supervised Texture Classification.” IEEE Transactions on Image Processing 17, no. 8: 1399–1405.
Chu, J., Z. Guo, and L. Leng. 2018. “Object Detection Based on Multi‐Layer Convolution Feature Fusion and Online Hard Example Mining.” IEEE Access 6: 19959–19967.
Dong, Y., J. Feng, L. Liang, L. Zheng, and Q. Wu. 2017. “Multiscale Sampling‐Based Texture Image Classification.” IEEE Signal Processing Letters 24, no. 5: 614–618.
Dong, Y., J. Feng, C. Yang, X. Wang, L. Zheng, and J. Pu. 2018. “Multi‐Scale Counting and Difference Representation for Texture Classification.” Visual Computer 34, no. 10: 1315–1324.
Dong, Y., and J. Ma. 2011. “Contourlet‐Based Texture Classification With Product Bernoulli Distributions.” In Advances in Neural Networks—ISNN, vol. 6676, 9–18. Springer.
Dong, Y., and J. Ma. 2012. “Texture Classification Based on Contourlet Sub Band Clustering.” In Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence, 421–426. Springer.
Dong, Y., and J. Ma. 2018. “Multiscale Counting and Difference Representation for Texture Classification.” Visual Computer 34, no. 10: 1315–1324.
Dong, Y., T. Wang, C. Yang, et al. 2019. “Locally Directional and Extremal Pattern for Texture Classification.” IEEE Access 7: 87931–87942.
Dong, Y., H. Wu, X. Li, C. Zhou, and Q. Wu. 2018. Multiscale Symmetric Dense Micro‐Block Difference for Texture Classification. IEEE Transactions on Circuits and Systems for Video Technology. https://doi.org/10.1109/TCSVT.2018.2883825.
Du, C., and S. Gao. 2017. “Image Segmentation‐Based Multi‐Focus Image Fusion Through Multi‐Scale Convolutional Neural Network.” IEEE Access 5: 15750–15761.
El Merabet, Y., Y. Ruichek, and A. El Idrissi. 2019. “Attractive‐and‐Repulsive Center‐Symmetric Local Binary Patterns for Texture Classification.” Engineering Applications of Artificial Intelligence 78: 158–172.
Fernández, A., M. X. Álvarez, and F. Bianconi. 2013. “Texture Description Through Histograms of Equivalent Patterns.” Journal of Mathematical Imaging and Vision 45, no. 1: 76–102.
Górriz, J. M., J. Ramírez, J. Suckling, et al. 2017. “Case‐Based Statistical Learning: A Non‐Parametric Implementation With a Conditional‐Error Rate SVM.” IEEE Access 5: 11468–11478.
Guo, X., Y. Li, and H. Ling. 2017. “LIME: Low‐Light Image Enhancement via Illumination Map Estimation.” IEEE Transactions on Image Processing 26, no. 2: 982–993.
Guo, Z., L. Zhang, and D. Zhang. 2010. “A Completed Modeling of Local Binary Pattern Operator for Texture Classification.” IEEE Transactions on Image Processing 19, no. 6: 1657–1663.
Hassner, T., S. Filosof, V. Mayzels, and L. Zelnik‐Manor. 2017. “Sifting Through Scales.” IEEE Transactions on Pattern Analysis and Machine Intelligence 39, no. 7: 1431–1443.
Hazgui, M., H. Ghazouani, and W. Barhoumi. 2022. “Genetic Programming‐Based Fusion of HOG and LBP Features for Fully Automated Texture Classification.” Visual Computer 38, no. 2: 457–476.
He, K., X. Zhang, S. Ren, and J. Sun. 2016. “Deep Residual Learning for Image Recognition.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 770–778. IEEE Explore.
Hong, X., G. Zhao, M. Pietikäinen, and X. Chen. 2014. “Combining LBP Difference and Feature Correlation for Texture Description.” IEEE Transactions on Image Processing 23, no. 6: 2557–2568.
Hu, S., J. Li, H. Fan, S. Lan, and Z. Pan. 2024. “Scale and Pattern Adaptive Local Binary Pattern for Texture Classification.” Expert Systems With Applications 240: 122403.
Ji, L., Y. Ren, G. Liu, and X. Pu. 2017. “Training‐Based Gradient LBP Feature Models for Multiresolution Texture Classification.” IEEE Transactions on Cybernetics 48, no. 9: 2683–2696.
Jiang, N., J. Xu, W. Yu, and S. Goto. 2013. “Gradient Local Binary Patterns for Human Detection.” In In 2013 IEEE International Symposium on Circuits and Systems (ISCAS), 978–981. IEEE.
Kannala, J., and E. Rahtu. 2012. “Bsif: Binarized Statistical Image Features.” In Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), 1363–1366. IEEE.
Karthikeyan, V., and S. S. Priyadharsini. 2024. “Text‐Independent Voiceprint Recognition via Compact Embedding of Dilated Deep Convolutional Neural Networks.” Computers and Electrical Engineering 118: 109408.
Karthikeyan, V., E. Raja, and K. Gurumoorthy. 2024. “Denoising Convolutional Neural Network With Energy‐Based Attention for Image Enhancement.” Journal of Applied Analysis and Computation 14, no. 4: 1893–1914.
Karthikeyan, V., and S. Suja Priyadharsini. 2024. “A Stacked Convolutional Neural Network Framework With Multi‐Scale Attention Mechanism for Text‐Independent Voiceprint Recognition.” Pattern Analysis and Applications 27, no. 2: 1–15.
Khadiri, E., I, Y. E. Merabet, A. S. Tarawneh, Y. Ruichek, D. Chetverikov, and R. Touahni. 2021. “Petersen Graph Multi‐Orientation Based Multi‐Scale Ternary Pattern (PGMO‐MSTP): An Efficient Descriptor for Texture and Material Recognition.” In IEEE Transactions on Image Processing, vol. 30, 4571–4586. IEEE. https://doi.org/10.1109/TIP.2021.3070188.
Khadiri, I. E., A. Chahi, Y. E. Merabet, Y. Ruichek, and R. Touahni. 2018. “Local Directional Ternary Pattern: A New Texture Descriptor for Texture Classification.” Computer Vision and Image Understanding 169: 14–27.
Khadiri, I. E., M. Kas, Y. El Merabet, Y. Ruichek, and R. Touahni. 2018. “Repulsive‐and‐Attractive Local Binary Gradient Contours: New and Efficient Feature Descriptors for Texture Classification.” Information Sciences 467: 634–653.
Khan, F. S., R. M. Anwer, J. Van De Weijer, M. Felsberg, and J. Laaksonen. 2015. “Compact Color–Texture Description for Texture Classification.” Pattern Recognition Letters 51: 16–22.
Lan, S., J. Li, S. Hu, H. Fan, and Z. Pan. 2024. “A Neighbourhood Feature‐Based Local Binary Pattern for Texture Classification.” Visual Computer 40, no. 5: 3385–3409.
Lategahn, H., S. Gross, T. Stsehle, and T. Aach. 2010. “Texture Classification by Modelling Joint Distributions of Local Patterns With Gaussian Mixtures.” IEEE Transactions on Image Processing 19, no. 6: 1548–1557.
Lehmann, F. 2011. “Turbo Segmentation of Textured Images.” IEEE Transactions on Pattern Analysis and Machine Intelligence 33, no. 1: 16–29.
Liu, L., P. Fieguth, G. Kuang, and H. Zha. 2011. “Sorted Random Projections for Robust Texture Classification.” In 2011 International Conference on Computer Vision, 391–398. IEEE.
Liu, L., S. Lao, P. W. Fieguth, Y. Guo, X. Wang, and M. Pietikäinen. 2016. “Median Robust Extended Local Binary Pattern for Texture Classification.” IEEE Transactions on Image Processing 25, no. 3: 1368–1381.
Lu, Y., and D. Song. 2015. “Visual Navigation Using Heterogeneous Landmarks and Unsupervised Geometric Constraints.” IEEE Transactions on Robotics 31, no. 3: 736–749.
Mohanaiah, P., P. Sathyanarayana, and L. GuruKumar. 2013. “Image Texture Feature Extraction Using GLCM Approach.” International Journal of Scientific and Research Publications 3, no. 5: 1–5.
Nanni, L., S. Brahnam, and A. Lumini. 2012. “A Simple Method for Improving Local Binary Patterns by Considering Nonuniform Patterns.” Pattern Recognition 45, no. 10: 3844–3852.
Ojala, T., M. Pietikäinen, and D. Harwood. 1996. “A Comparative Study of Texture Measures With Classification Based on Featured Distributions.” Pattern Recognition 29, no. 1: 51–59.
Ojala, T., M. Pietikäinen, and T. Mäenpää. 2002. “Multiresolution Gray‐Scale and Rotation Invariant Texture Classification With Local Binary Patterns.” IEEE Transactions on Pattern Analysis and Machine Intelligence 24, no. 7: 971–987.
Ouslimani, F., A. Ouslimani, and Z. Ameur. 2025. “Robust Directional Median Pattern for Noisy Texture Classification.” Multimedia Tools and Applications 84, no. 1: 131–145.
Pillai, A., R. Soundrapandiyan, S. Satapathy, S. C. Satapathy, K. H. Jung, and R. Krishnan. 2018. “Local Diagonal Extrema Number Pattern: A New Feature Descriptor for Face Recognition.” Future Generation Computer Systems 81: 297–306.
Rainer, G., A. Ghosh, W. Jakob, and T. Weyrich. 2020. “Unified Neural Encoding of BTFs.” Computer Graphics Forum 39, no. 2: 167–178.
Ren, J., X. Jiang, and J. Yuan. 2013. “Noise‐Resistant Local Binary Pattern With an Embedded Error‐Correction Mechanism.” IEEE Transactions on Image Processing 22, no. 10: 4049–4060.
Rezaei, M., M. Saberi, and S. F. Ershad. 2011. “Texture Classification Approach Based on Combination of Random Threshold Vector Technique and Co‐Occurrence Matrixes.” In Proceedings of 2011 International Conference on Computer Science and Network Technology, vol. 4, 2303–2306. IEEE.
Saniei, T., M. Kianersi, and S. Fekri‐Ershad. 2024. “Assessing Relations Among Visual Variables in Hotel Lobbies Using Deep Learning.” Interiority 7, no. 2: 175–198.
Satpathy, A., X. Jiang, and H. L. Eng. 2014. “LBP‐Based Edge‐Texture Features for Object Recognition.” IEEE Transactions on Image Processing 23, no. 5: 1953–1964.
Shao, J., C. C. Loy, and X. Wang. 2017. “Learning Scene‐Independent Group Descriptors for Crowd Understanding.” IEEE Transactions on Circuits and Systems for Video Technology 27, no. 6: 1290–1303.
Sima, J., Y. Dong, T. Wang, L. Zheng, and J. Pu. 2018. “Extended Contrast Local Binary Pattern for Texture Classification.” International Journal of New Technology and Research 4, no. 3: 263120.
Su, H., J. Chen, Z. Li, H. Meng, and X. Wang. 2024. “The Fusion Feature Wavelet Pyramid Based on FCIS and GLCM for Texture Classification.” International Journal of Machine Learning and Cybernetics 15, no. 5: 1907–1926.
Su, H., and C. Jung. 2018. “Perceptual Enhancement of Low Light Images Based on Two‐Step Noise Suppression.” IEEE Access 6: 7005–7018.
Subrahmanyam, M., R. P. Maheshwari, and R. Balasubramanian. 2012. “Local Maximum Edge Binary Patterns: A New Descriptor for Image Retrieval and Object Tracking.” Signal Processing 92, no. 6: 1467–1479.
Sun, X., J. Wang, M. F. She, and L. Kong. 2013. “Scale Invariant Texture Classification via Sparse Representation.” Neurocomputing 122: 338–348.
Szegedy, C., W. Liu, Y. Jia, et al. 2015. “Going Deeper With Convolutions.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1–9. IEEE Explore.
Tan, X., and B. Triggs. 2010. “Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions.” IEEE Transactions on Image Processing 19, no. 6: 1635–1650.
Tang, K., S. Peng, and X. Chen. 2017. “3D Object Recognition in Cluttered Scenes With Robust Shape Description and Correspondence Selection.” IEEE Access 5: 1833–1845.
Teixeira, L. O., D. Bertolini, L. S. Oliveira, G. D. Cavalcanti, and Y. M. Costa. 2025. “Triplet Dissimilarity: A Texture Classification Approach Using Dissimilarity and Siamese Networks.” Soft Computing 29, no. 11–12: 1–18.
Tiwari, S., A. K. Sharma, I. Abdul Aziz, et al. 2025. “Investigations on Segmentation‐Based Fractal Texture for Texture Classification in the Presence of Gaussian Noise.” PLoS One 20, no. 1: e0315135.
Tuncer, T., S. Dogan, and F. Ertam. 2019. “A Novel Neural Network Based Image Descriptor for Texture Classification.” Physica A: Statistical Mechanics and Its Applications 526: 120955.
Vácha, P., and M. Haindl. 2011. “Texture Recognition Using Robust Markovian Features.” In Internatinoal Workshop on Computational Intelligence for Multimedia Understanding, 126–137. Springer.
Varma, M., and A. Zisserman. 2005. “A Statistical Approach to Texture Classification From Single Images.” International Journal of Computer Vision 62, no. 1: 61–81.
Varun Prakash, R., V. Karthikeyan, S. Vishali, and M. Karthika. 2024. “Multi‐Level LSTM Framework With Hybrid Sonic Features for Human–Animal Conflict Evasion.” Visual Computer 41: 1–17.
Velayuthapandian, K., N. Murugan, and S. Paramasivan. 2024. “End‐to‐End CNN Conceptual Model for a Biometric Authentication Mechanism for ATM Machines.” Discover Electronics 1, no. 1: 26.
Velayuthapandian, K., M. Veyilraj, and M. A. Jayakumaraj. 2024. “An Intelligent Parking Allocation Framework for Digital Society 5.0.” Intelligent Decision Technologies 18, no. 3: 2145–2159.
Wang, W., J. Shen, R. Yang, and F. Porikli. 2018. “Saliency‐Aware Video Object Segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40, no. 1: 20–33.
Wang, Y., Y. Shao, Y. Quan, and Y. Liu. 2017. “Noise Removal of Low‐Dose CT Images Using Modified Smooth Patch Ordering.” IEEE Access 5: 26092–26103.
Xie, J., L. Zhang, J. You, and S. Shiu. 2015. “Effective Texture Classification by Texton Encoding Induced Statistical Features.” Pattern Recognition 48, no. 2: 447–457.
Xu, X., and B. Li. 2025. “Multi Scale Supervised Entropy Weighted Binary Pattern for Texture Classification.” Scientific Reports 15, no. 1: 26087.
Yavuz, B. C., N. Yurtay, and O. Ozkan. 2018. “Prediction of Protein Secondary Structure With Clonal Selection Algorithm and Multilayer Perceptron.” IEEE Access 6: 45256–45261.
Yuan, Y., L. Mou, and X. Lu. 2015. “Scene Recognition by Manifold Regularized Deep Learning Architecture.” IEEE Transactions on Neural Networks and Learning Systems 26, no. 10: 2222–2233.
Zhang, J., H. Zhao, and J. Liang. 2013. “Continuous Rotation Invariant Local Descriptors for Texton Dictionary‐Based Texture Classification.” Computer Vision and Image Understanding 117, no. 1: 56–75.
Zhang, L., Z. Zhou, and H. Li. 2012. “Binary Gabor Pattern: An Efficient and Robust Descriptor for Texture Classification.” In 2012 19th IEEE International Conference on Image Processing, 81–84. IEEE.
Zhang, T., S. Liu, C. Xu, B. Liu, and M.‐H. Yang. 2018. “Correlation Particle Filter for Visual Tracking.” IEEE Transactions on Image Processing 27, no. 6: 2676–2687.
Zhao, Y., D.‐S. Huang, and W. Jia. 2012. “Completed Local Binary Count for Rotation Invariant Texture Classification.” IEEE Transactions on Image Processing 21, no. 10: 4492–4497.
Zhu, H., K.‐V. Yuen, L. Mihaylova, and H. Leung. 2017. “Overview of Environment Perception for Intelligent Vehicles.” IEEE Transactions on Intelligent Transportation Systems 18, no. 10: 2584–2601.
Contributed Indexing:
Keywords: directional pattern; extremal pattern; local pattern; spatial relationship intensity; texture classification; texture representation
Entry Date(s):
Date Created: 20251019 Date Completed: 20251019 Latest Revision: 20251019
Update Code:
20260130
DOI:
10.1111/jtxs.70049
PMID:
41111005
Database:
MEDLINE
*Further Information*
*Image texture refers to the visual patterns, variations, or configurations of pixel intensities within an image. Classifying textures is a fundamental goal in computer vision, applicable in areas ranging from medical picture analysis to distant sensing. Throughout the years, numerous strategies have been proposed to address this challenge; however, recent advances in deep learning have significantly transformed the subject. The proposed work delineates reliable and resilient local descriptors termed Texture Classification using Effective Texture Descriptors (TCETD), which integrates Locally Directional and Extremal Pattern (LDEP) with Gray-Level Co-occurrence Matrix (GLCM) to effectively acquire directional, extremum statistics, and spatial relationships among pixel intensities. To communicate directions related to the local area, it first obtains the directional local difference count pattern (DLDCP), which is divided into symmetric and asymmetric positions. By integrating the extremum location, differential, and compression pattern from adjacent sites, we extract the neighbor's extremum-related local pattern to acquire the extremum data generated by the initial segment. The two elements are combined to create the LDEP. The GLCM extracts spatial correlations, pixel intensity patterns, and features based on the distance and angle of pixels within an image. This descriptor can be utilized alongside the LDEP approach to offer a more thorough and resilient representation of the picture texture features, hence enhancing classification accuracy. The outcomes of experiments performed on three notable texture image databases-Klyberg (Stex), Kth-tips2-a, and CUReT-exhibit comparable correct classification rates of 97.91%, 93.82%, and 97.25%, respectively. These rates were achieved using our recently proposed TCETD descriptor under diverse conditions, including rotational and illumination variations, scale differences, and viewpoint alterations, in contrast to traditional methods for classifying texture images. The efficacy of the proposed strategy is corroborated using the Bonn BTF dataset, and the recommended method demonstrated superior performance.
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