Open Access   Article Go Back

Feature Extraction of Medical Images Using Moment Invariants

V.V. Agarkar1

Section:Research Paper, Product Type: Journal Paper
Volume-9 , Issue-12 , Page no. 30-33, Dec-2021

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v9i12.3033

Online published on Dec 31, 2021

Copyright © V.V. Agarkar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: V.V. Agarkar, “Feature Extraction of Medical Images Using Moment Invariants,” International Journal of Computer Sciences and Engineering, Vol.9, Issue.12, pp.30-33, 2021.

MLA Style Citation: V.V. Agarkar "Feature Extraction of Medical Images Using Moment Invariants." International Journal of Computer Sciences and Engineering 9.12 (2021): 30-33.

APA Style Citation: V.V. Agarkar, (2021). Feature Extraction of Medical Images Using Moment Invariants. International Journal of Computer Sciences and Engineering, 9(12), 30-33.

BibTex Style Citation:
@article{Agarkar_2021,
author = {V.V. Agarkar},
title = {Feature Extraction of Medical Images Using Moment Invariants},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2021},
volume = {9},
Issue = {12},
month = {12},
year = {2021},
issn = {2347-2693},
pages = {30-33},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5426},
doi = {https://doi.org/10.26438/ijcse/v9i12.3033}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i12.3033}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5426
TI - Feature Extraction of Medical Images Using Moment Invariants
T2 - International Journal of Computer Sciences and Engineering
AU - V.V. Agarkar
PY - 2021
DA - 2021/12/31
PB - IJCSE, Indore, INDIA
SP - 30-33
IS - 12
VL - 9
SN - 2347-2693
ER -

VIEWS PDF XML
259 355 downloads 153 downloads
  
  
           

Abstract

Automatic shape recognition and feature extraction from images has become very significant in today’s digital word as the use of digital images has grown exponentially over the last few decades. Image processing is a method which uses computer algorithms to extract various useful information from the digital images. Image processing mainly involves visualization, pattern recognition, feature extraction, classification etc. Moment invariants have been used as features for image processing. Moments can provide features of an object that uniquely represent its shape. These features are independent of translation, scale and rotation. The aim of this paper was to investigate the usefulness of moment invariants for the feature extraction from digital images. Two experiments were conducted to test the moment invariant for rotation invariance and scale invariance. The study found that most of the seven features had minor fluctuations when rotating or scaling the image.

Key-Words / Index Term

Moment Invariant, Image processing, Pattern recognition, Feature extraction

References

[1] R. E. Twogood and F. G. Sommer, “Digital Image Processing”, in IEEE Transactions on Nuclear Science, vol. 29, no. 3, pp. 1075-1086, 1982.
[2] Z. Hu, H. Zheng and J. Gui, “A Novel Interactive Image Processing Approach for DICOM Medical Image Data”, 2nd International Conference on Biomedical Engineering and Informatics, pp. 1-4, 2009.
[3] Huang Zhihu and Jinsong Leng, “Analysis of Hu`s moment invariants on image scaling and rotation”, 2nd International Conference Computer Engineering and Technology (ICCET), vol. 7, 2010.
[4] Jan Flusser, “Moment Invariants in Image Analysis”, Proceedings of World Academy of Science, Engineering and Technology, Vol 11, pp. 196-201, 2006.
[5] M. K. Hu, “Visual Pattern Recognition by Moment Invariants”, IRE Trans. on Information Theory, Vol. IT-8, pp. 179-187, 1961.
[6] R. Y. Wong and E. L. Hall, “Scene Matching with Invariant Moments”, Computer Graphics and Image Processing, vol. 8, pp. 16–24, 1978.
[7] J. Flusser and T. Suk, “Affine moment invariants: A new tool for character recognition”, Pattern Recognition Letters, vol. 15, pp. 433–436, 1994.
[8] S. O. Belkasim, M. Shridhar, and M. Ahmadi, “Pattern recognition with moment invariants: a comparative study and new results”, Pattern Recognition, vol. 24, pp. 1117–1138, 1991.
[9] T. H. Reiss, “The revised fundamental theorem of moment invariants”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, pp. 830–834, 1991.
[10] L. van Gool, T. Moons, and D. Ungureanu, “Affine/photometric invariants for planar intensity patterns”, in Proc. 4th ECCV’96, Springer, vol. LNCS 1064, pp. 642–651, 1996.
[11] Jan Flusser, Barbara Zitova, Tomas Suk, “Moments and Moment Invariants in Pattern Recognition”, Wiley Publications, 2009.
[12] M. Fachrurrozi, Saparudin, A. Lestari, O. Arsalan, Samsuryadi and Ermatita, “Multiple Face Image Feature Extraction Using Geometric Moment Invariants Method”, International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), pp. 219-224, 2019.
[13] B. P. H. K. M. D. Senarathna and R. M. T. P. Rajakaruna, “Feature Descriptor for Sri Lankan Batik Patterns Using Hu Moment Invariants and GLCM”, 10th International Conference on Information and Automation for Sustainability (ICIAfS), pp. 197-202, 2021.
[14] S. Sharma and P. Khanna, “Computer-Aided Diagnosis of Malignant Mammograms using Zernike Moments and SVM”, Journal of digital imaging vol. 28, 1, pp. 77-90, 2015.
[15] S. Urooj and S. P. Singh, “Geometric invariant feature extraction of medical images using Hu`s invariants”, 3rd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 1560-1562, 2016.
[16] Y. M. Vaidya, B. S. V. Swati and N. Kantipudi, “Moment Invariants based feature techniques for segmentation of retinal images using supervised method”, International Conference on Industrial Instrumentation and Control (ICIC), pp. 1373-1377, 2015.
[17] Y. Jusman, M. K. Anam, S. Puspita and E. Saleh, “Machine Learnings of Dental Caries Images based on Hu Moment Invariants Features”, International Seminar on Application for Technology of Information and Communication (iSemantic), pp. 296-299, 2021.
[18] Laura Keyes and Adam Winstanley, “Applying Computer Vision Techniques To Topographic Objects”, International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3, Amsterdam, pp. 480-487, 2000.
[19] Dehghan, M. and Faez, K., “Farsi Handwritten Character Recognition with Moment Invariants”, International Conference on Digital Signal Processing, Vol. 2, pp. 507-510, 1997.
[20] V. V. Agarkar, “Analysis of Sperm Morphology in Microscopic Images based on Moment Invariants”, M. Phil. Dissertation, Alagappa University, Karaikudi, 2009.