A Study on Various Image Feature Extraction Techniques

Authors(2) :-Merllin Ann George, Dr L. C. Manikandan

Feature Extraction is the technique of extracting quantitative information from a image. Feature plays a very important role in the area of image processing. The purpose of feature extraction technique in image processing is to represent the image in its compact and unique form of single values or matrix vector. Feature extraction techniques are helpful in various image processing applications e.g. character recognition. As features define the behavior of an image, they show its place in terms of storage taken, efficiency in classification and obviously in time consumption also. The aim of this paper is to give the overview of image feature extraction techniques for young learners and researchers.

Authors and Affiliations

Merllin Ann George
M.Tech. Student, Department of CSE, Musaliar College of Engineering and Technology, Pathanamthitta, Kerala, India
Dr L. C. Manikandan
Professor & HoD, Department of CSE, Musaliar College of Engineering and Technology, Pathanamthitta, Kerala, India

Feature Extraction, Zoning, Characteristic Loci, Gray-level, Fourier Transforms, Walsh Hadamard Tansform, Rapid transform, Gabor Transform, Hough Transform

  1. Isabelle Guyon and Andre Elisseeff, “An Introduction to Feature Extraction”, pp 1-25, Studfuzz 207, Springer, 2006
  2. Neeraj Pratap1 and Dr. Shwetank Arya “A Review of Devnagari Character Recognition from Past to Future” International Journal of Computer Science and Telecommunications Volume 3, Issue 6, June 2012].
  3. Gaurav kumar and Pradeep Kumar Phatia, “A Detailed Review of Feature Extraction in Image Processing Systems”, International Conference on Advanced Computing & Communication Technologies, IEEE, 2014
  4. S. S.Wang, P. C. Chen, and W. G. Lin, “Invariant pattern recognition by moment Fourier descriptor,” Pattern Recognit., vol. 27, pp. 1735–1742, 1994.
  5. X. Zhu, Y. Shi, and S. Wang, “A new algorithm of Connected character image based on Fourier transform,” in Proc. 5th Int. Conf. Document Anal. Recognition. Bangalore, India, 1999, pp. 788–791.
  6. C.Y. Suen, M. Berthod and S. Mori, Automatic Recogniti”on of Handprinted-Characters _ the State of the Art in Proceedings of the IEEE, Vol: 68, No: 4, 1980.
  7. Nariz Arica” An Offline Character Recognition System for Free Style Handwritting” 1998.
  8. S.S.Pandey, Manu Pratap Singh and Vikas Pandey, “Image Transformation and Compression using Fourier Transformation”, International Journal of Current Engineering and Technology, Vol. 5, No. 2, April 2015.
  9. M. A. Mohamed, P. Gader, “Handwritten Word Recognition Using Segmentation-Free Hidden Markov Modeling and Segmentation Based Dynamic Programming Techniques”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol.18, no.5, pp.548-554, 1996.
  10. Neelu Arora and Mrs. G. Sarvani, “A Review Paper on Gabor Filter Algorithm and its Application”, IJARECE, Vol 6, Sept 2017.
  11. Biswajit Pathak and Debajyoti Barooah, “Texture Analysis Based on the Gray-Level Co-occurrence Matrix Considering Possible Orientations”, IJAREEIE, Vol. 2, September 2013.
  12. Biswajit Sit and Md. Iqbal Quraishi, “A Review Paper on Hough Transform and it’s Applications in Image Processing”, IJIRSET, Vol. 5, October 2016.
  13. Nafiz Arica, “An Offline Character Recognition System for free style Handwriting”, pp.1- 123, Sept. 2008.
  14. Anshul Gupta, Manisha Srivastava, “Offline Handwritten Character Recognition”, pp. 1-27, April 2011.
  15. R.M. Haralick, K. Shanmugam, I. Dinstein, “Textural Features for Image Classification”, IEEE Trans. on Systems, Man and Cybernetics (1973)610 – 621.
  16. M. A. Mohamed, P. Gader, “Handwritten Word Recognition Using Segmentation-Free Hidden Markov Modeling and Segmentation Based Dynamic Programming Techniques”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol.18, no.5, pp.548-554, 1996.
  17. Sandhya Arora, Meghnad Saha, Debotosh Bhattacharjee, Mita Nasipuri, “Combining Multiple Feature Extraction Techniques for Handwritten Devnagari Character Recognition”, IEEE Region 10 Colloquium and the Third ICIIS, pp. 1-6, Dec. 2008
  18. Nariz Arica” An Offline Character Recognition System for Free Style Handwritting” 1998.
  19. Cheng-Lin Liu, “Normalization-Cooperated Gradient Feature Extraction for Handwritten Character Recognition”, IEEE Transaction on pattern analysis and machine intelligence, vol. 29, no. 8, Aug. 2007.
  20. R. G. Casey, E. Lecolinet, “A Survey of Methods and Strategies in Character Segmentation”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol.18, no.7, pp.690-706, 1996.
  21. C. Goswami & A. K. Chan , Fundamental of Wavelets Theory, Algorithms & Application 2nd Edition, Wiley, 2011.

Publication Details

Published in : Volume 5 | Issue 5 | September-October 2019
Date of Publication : 2019-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 151-157
Manuscript Number : CSEIT1195528
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Merllin Ann George, Dr L. C. Manikandan, "A Study on Various Image Feature Extraction Techniques", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 5, pp.151-157, September-October-2019. Available at doi : https://doi.org/10.32628/CSEIT1195528
Journal URL : https://res.ijsrcseit.com/CSEIT1195528 Citation Detection and Elimination     |      |          | BibTeX | RIS | CSV

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