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Local Binary Patterns and Its Extended Variants

Hardeep Singh, Gagandeep .

Abstract


ABSTRACT

This paper focuses on the Local Binary Patterns and its various important variants. LBP is a non-parametric descriptor and used to extract, analyze, recognize and classify the different modality images. It summarizes the local patterns of image characteristics efficiently. LBP and its many extended versions have been extensively used in numerous applications of computer vision, image processing, pattern recognition and biomedical field in recent years. Very discriminative and computationally efficient local texture descriptors based on local binary patterns (LBPs) is studied, which led to significant progress in applying texture methods to different problems and applications. The efficiency and usability of the LBP operator and its success in various real world applications has inspired the development of much new powerful LBP variants. In this paper, the important extensions of LBP using local structure of the image are extensively reviewed.

 

Keywords: Local binary pattern, texture, LBP, LTP


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REFERENCES

Ojala T, Pietikainen M, Harwood D, “Performance evaluation of texture measures with classification based on kullback discrimination of distributions,” Pattern recognition, pp. 1: 582-585,1994.

Trygve Randen, John Hakon Husoy, “Filtering for texture classification: a comparative study,” volume 21, IEEE, pp. 291-310, 1999.

Maenpaa T, “The local binary pattern approach to texture analysis-extensions and applications,” Infotech Oulu, University of Oulu, Finland, 2003.

Ojala T, Pietikainen M, Harwood D, “A comparative study of texture measures with classification based on feature distributions,” pattern recognition 29(1), pp. 51-59, 1996.

Ojala T, Pietikainen M, Maenpaa T, “Gray scale and rotation invariant texture classification with local binary patterns,” In: European conference on computer vision, lecture notes in computer science, volume 1842, Springer Berlin, pp. 404-420, 2000..

Ojala T, Pietikainen M, Valkealahti K, Oja E, “Texture discrimination with multidimensional distributions of signed gray level differences,” Pattern Recognition 34: pp. 727-739, 2001.

Ojala T, Pietikainen M, Maenpaa T, “Multiresolution gray-scale and rotation invariant texture classification with local binary patterns,” IEEE Trans. Pattern Anal. Mach. Intel 24(7): pp. 971-987, 2002.

Pietikainen M, Ahonen T, Hadid A, “Face recognition with local binary patterns,” in Computer vision-ECCV Springer, pp. 469-481, 2004.

Pietikainent M, Maenpa T “Texture analysis with local binary patterns,” Handbook of pattern recognition and vision, world scientific, Signapore 3rd edition, pp. 197-216, 2005.

Pietkainen M, Zho G, “Dynamic texture recognition using local binary patterns with application to facial expression,” Pattern analysis and machine intelligence, IEEE Transactions on, volume 29, no.6, pp. 915-928, 2007.

Wang X, Han T X, Yan S, “A hog-LBP human detector with partial occlusion handling in computer vision,” IEEE, 12th International conference on, pp. 32-39, 2009.

Pietikainen M, Hadid A, Zhao G, Ahonen T, “Computer vision using local binary patterns,” Springer, London 2011.

Guo Z, Zhang L, Zhang D, “A completed modeling of local binary pattern operator for texture classification” IEEE, Trans. image process volume e Pub, 2010.

Sajida Parveen, Nadeem Naeem, Jherna Devi, “Review on local binary pattern texture descriptor and its variants,” International journal of advanced research. Int. J. Adv.Res.5 (5) pp. 708-717, 2017.

Tan X, Triggs B, “Enhanced local texture feature sets for face recognition under difficult lighting conditions,” Anal. Model faces gestures, LNCS 4778, pp. 168-182, 2007.

Rassem Taha H, Bee Ee Khoo, "Completed local ternary pattern for rotation invariant texture classification," The scientific world-journal, 2014.

Yang, Wankou, Changyin Sun, "Face recognition using improved local texture patterns," Intelligent control and automation (WCICA), 9th world congress on, IEEE, 2011.

Akhloufi, Moulay, Abdelhakim Bendada, "Locally adaptive texture features for multispectral face recognition," Systems man and cybernetics (SMC), IEEE, International conference on, 2010.

Pietkainen M, Heikkil M, Schmid C, “Description of interest regions with local binary patterns,” Pattern recognition, pp. 42: 425-436, 2009.

Pietkainen M, Guo Y, Zhao G, “Texture classification using a linear configuration model based descriptor,” In: Proceedings of the British machine vision conference MVC, Dundee, UK, pp. 119.1-119.10, 2011.

Gagan Deep, Lakhwinder Kaur, Savita Gupta, “Biomedical image retrieval using microscopic configuration with local structural information,” Sadhana 43:20, volume v, Indian academy of sciences, 2018.

Kokare M, Biswas P K, Chatterji B N, “Texture image retrieval using rotated wavelet filters,” pattern recognition, Lett 28: pp. 1240-1249, 2007.

Subramanyam Murala, Maheshwari R P, Balasubramanian R, “Directional local extrema patterns: a new descriptor for content based image retrieval,” published online: Springer-Verlag London limited, pp. 191-203, 2012.

Andrew Fitzgibbon, ‎Svetlana Lazebnik, ‎Pietro Perona, “Insensitive texture classification using local phase quantization,” ‎Computers, 2012.

Subramanyam Murala, Maheshwari R P, Balasubramanian R, “Local tetra patterns: a new feature descriptor for content-based image retrieval,” IEEE-Transactions on image processing volume 2 Issue: 5, pp. 2874-2886, 2012..

Subramanyam Murala, Maheshwary R P, Balasubramanian R, “Local maximum edge binary patterns: a new descriptor for image retrieval and object tracking,” Signal processing- 92(6), pp. 1467-1479, 2012.

Subrmanyam Murala, Maheshwari R P, Balasubramanian R, “Directional binary wavelet patterns for biomedical image indexing and retrieval,” J. Med. Syst. 36(5): pp. 2865-2879, 2012.

Subramnyam Murala, Jonathan W Q, “Peak valley edge patterns: a new descriptor for biomedical image indexing and retrieval,” In: Proceedings of the IEEE, Conference on computer vision and pattern recognition workshops (CVPRW), pp. 444-449, 2013.

Subramanyam Murala, Jonathan Q M, J Wu, “Local ternary co-occurrence patterns: a new feature descriptor for MRI and CT image retrieval,” pp. 399-412, 2013.

Subramanyam Murala, J Wu, “Local mesh pattern verses local binary pattern-biomedical image indexing and retrieval,” IEEE, Journal of biomedical and health informatics, 18(3), pp. 929-938, 2014.

Subramanyam Murala, Balasubramanian R, “Local extrema co-occurrence pattern for color and texture image retrieval,” Publication: Neurocomputing, 2015.

Gagan Deep, Lakhwinder Kaur, Savita Gupta, “Directional local ternary quantized extrema pattern: a new descriptor for biomedical image indexing and retrieval,” Engineering science and technology an international-journal, 19, pp. 1895-1909, 2016.

Gagan Deep, Lakhwinder Kaur, Savita Gupta, “Biomedical image indexing and retrieval descriptors: a comparative study,” Procedia computer science 85, pp. 954-961, 2016.

Gagan Deep, Lakhwinder Kaur, Savita Gupta, “Local mesh ternary patterns: a new descriptor for MRI and CT biomedical image indexing and retrieval,” Computer methods in biomechanics and biomedical engineering (CMBBE): imaging & visualization, 2016.

Dey M, Balasubramanian R, Verma M, “A novel color-and texture-based image retrieval technique using multiresolution local extrema peak valley pattern and RGB color histogram,” Pattern Anal Appl, pp. 19:1159–1179, 2016.

Subrahmanyam Murala, Prithaj Banerjee, Ayan Kumar, Bhunia, Avirup Bhattacharyya, Partha Pratim Roy, “Local neighborhood intensity pattern -a new texture feature descriptor for image retrieval,” 2017.

Sree Vidya B, Chandra E, “Entropy based Local Binary Pattern feature extraction technique of multimodal biometrics as defence mechanism for cloud storage,” Alexandria University, Alexandria Engineering-journal, pp. 58: 103-114, 2019.

Ignace Tchangou Toudjeu, Jules-Raymond Tapamo, “Circular derivative local binary pattern feature description for facial expression recognition,” Advances in Electrical and Computer Engineering-journal, Volume 19, Number 1, pp. 51-56, 2019.

Srishti Gupta, Partha Pratim Roy, Debi Prosad Dogra, Byung Gyu Kim, “Retrieval of colour and texture images using local directional peak valley binary pattern,” Pattern analysis and applications, © Springer-Verlag London Ltd, part of Springer Nature journal, 2020.




DOI: https://doi.org/10.37628/ijoippr.v6i2.605

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