20May 2017

REVIEW ON LOCAL BINARY PATTERN (LBP) TEXTURE DESCRIPTOR AND ITS VARIANTS.

  • Department of Computer Systems Engineering, Quaid-e-Awamunivertersity of Engineering, Science and Technology, Nawabshah, Pakistan.
  • Department of Electronic Engineering, Quaid-e-Awamunivertersity of Engineering, Science and Technology, Nawabshah, Pakistan.
  • Department of Information Technology,Quaid-e-Awamunivertersity of Engineering, Science and Technology, Nawabshah, Pakistan.
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Local binary pattern and its variants have been extensively used in the numerous applications of various fields such as computer vision, pattern recognition, and texture analysis and etc. Comprehensive review based on the study of Local Binary Pattern and its variants is providing in this article. The detailed stat-of-art feature descriptors which are mostly used for number of application to analyze the textural properties have been discussed along with their pros and cons. The conclusion is made on the basis of their limitations and highlighted the gapes of recent variants of LBP texture descriptors.

  1. Chaudhuri, B. B., N. Sarkar, and P. Kundu. "Improved fractal geometry based texture segmentation technique." IEE Proceedings E (Computers and Digital Techniques)5 (1993): 233-242.
  2. Zhang, Jianguo, and Tieniu Tan. "Brief review of invariant texture analysis methods." Pattern recognition3 (2002): 735-747.
  3. Materka, Andrzej, and Michal Strzelecki. "Texture analysis methods?a review." Technical university of lodz, institute of electronics, COST B11 report, Brussels (1998): 9-11.
  4. M?aenp?a?a T &Pietik?ainen M (2005) Texture analysis with local binary patterns. Proc. C. Chen and P. Wang (eds.) Handbook of Pattern Recognition and Vision, World Scientific, Signapore, 3rd Edition, 197?216.
  5. He, D., Wang, L.: Texture unit, texture spectrum and texture analysis. In: Geoscience and Remote Sensing, Symposium (1989)
  6. Ojala, T., Pietikainen, M., Harwood, D.: Performance evaluation of texture measures with classification based on kullback discrimination of distributions. In: 12th IAPR International Conference (1994).
  7. Ojala, T., Pietik?inen, M., M?enp??, T.: Gray scale and rotation invariant texture classification with local binary patterns. In: European Conference on Computer Vision. Lecture Notes in Computer Science, vol. 1842, pp. 404?420. Springer, Berlin (2000)
  8. Ojala, T., Pietik?inen, M., Harwood, D.: A comparative study of texture measures with classification based on feature distributions. Pattern Recognit. 29(1), 51?59 (1996)
  9. Ojala T, Pietik?ainen M &M?aenp?a?a T (2002b) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7): 971?987.
  10. Pietik?Pietikainen, M., Hadid, A., Zhao, G., Ahonen, T.: Computer Vision Using Local Binary Patterns. Springer, London (2011)
  11. Guo, Z., Zhang, L., Zhang, D.: A completed modeling of local binary pattern operator for texture classification. EE Trans. Image Process. vol. ePub (2010)
  12. Tan, X., Triggs, B.: Enhanced local texture feature sets for face recognition under difficult lighting conditions. Anal. Model. Faces Gestures, LNCS 4778, 168?182 (2007)
  13. Rassem, Taha H., and Bee EeKhoo. "Completed local ternary pattern for rotation invariant texture classification." The Scientific World Journal 2014 (2014).
  14. Yang, Wankou, and Changyin Sun. "Face recognition using improved local texture patterns." Intelligent Control and Automation (WCICA), 2011 9th World Congress on. IEEE, 2011.
  15. Akhloufi, Moulay, and AbdelhakimBendada. "Locally adaptive texture features for multispectral face recognition." Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on. IEEE, 2010.
  16. Ibrahim, Mohammad, MdIftekharulAlamEfat, HumayunKayeshShamol, Shah MostafaKhaled, Mohammad Shoyaib, and M. Abdullah-Al-Wadud.(2014).Dynamic Local Ternary Pattern for Face Recognition and Verification.InInternational Conference on Computer Engineering and Applications, no. 8. 10-12 janary, Tenerife, Spain.
  17. Zhenyu, Wang, et al. "An enhanced Local Ternary Patterns method for face recognition." Control Conference (CCC), 2014 33rd Chinese. IEEE, 28-30 July, 2014, Nanjing, China

[Sajida Parveen, Nadeem Naeem and Jherna Devi (2017); REVIEW ON LOCAL BINARY PATTERN (LBP) TEXTURE DESCRIPTOR AND ITS VARIANTS. Int. J. of Adv. Res. 5 (May). 708-717] (ISSN 2320-5407). www.journalijar.com

Dr. Sajida Parveen
Quaid-e-awam University of Engineering, science and technology.

DOI:

Article DOI: 10.21474/IJAR01/4169      
DOI URL: https://dx.doi.org/10.21474/IJAR01/4169

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