A Survey of Image Processing and Identification Techniques


EOI: 10.11242/viva-tech.01.01.10

Download Full Text here



Citation

Sahil V. Khedaskar, Mohit A. Rokade, Bhargav R. Patil, Tatwadarshi P. N., "A Survey of Image Processing and Identification Techniques", VIVA-Tech IJRI Volume 1, Issue 1, Article 10, pp. 1-10, Oct 2018. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Image processing is always an interesting field as it gives enhanced visual data for human simplification and processing of image data for transmission and illustration for machine preception. Digital images are processed to give better solution using image processing. Techniques such as Gray scale conversion, Image segmentation, Edge detection, Feature Extraction, Classification are used in image processing. In this paper studies of different image processing techniques and its methods has been conducted. Image segmentation is the initial step in many image processing functions like Pattern recognition and image analysis which convert an image into binary form and divide it into different regions. The technique used for segmentation is Otsu’s method, K-means Clustering etc. For feature extraction feature vector in visual image is texture, shape and color. Edge detector with morphological operator enhances the clarity of image and noise free images. This paper also gives information about algorithm like Artificial Neural Network and Support Vector Mechanism used for image classification. The image is categorized into the receptive class by an ANN and SVM is used to compile all the categorized result. Overall the paper gives detail knowledge about the techniques used for image processing and identification.

Keywords

Extraction, Segmentation, Otsu’s method, K-means, Edge detection, ANN, SVM, Active Shape model(ASM), GLCM, SIFT, Genetic algorithm, BIM, RGB Colour, BIM, Vein algorithm.

References

  1. N. Petrellis, "A smart phone image processing application for plant disease diagnosis." In Modern Circuits and Systems Technologies (MOCAST), 2017 6th International Conference on, IEEE 2017, pp. 1-4.
  2. V. Kumar, T. Lal, P. Dhuliya, and Diwaker Pant. "A study and comparison of different image segmentation algorithms." In Advances in Computing, Communication, & Automation (ICACCA)(Fall), International Conference on, IEEE 2016, pp. 1-6.
  3. R. Radha, and S. Jeyalakshmi. "An effective algorithm for edges and veins detection in leaf images." In Computing and Communication Technologies (WCCCT), 2014 World Congress on, IEEE 2014, pp. 128-131.
  4. Y. Fang, X. Wang, P. Shi, C. Lin, and R. Zhai. "Automatic identification of two growth stages for rapeseed plant: Three leaf and four leaf stage." In Agro-Geoinformatics (Agro-geoinformatics), 2015 Fourth International Conference on,. IEEE 2015, pp. 148- 153.
  5. V. Singh and A. K. Misra. "Detection of unhealthy region of plant leaves using Image Processing and Genetic Algorithm." In Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in, IEEE 2015, pp. 1028-1032.
  6. A. Le Bris, T. Francois, and C. Nesrine, "Contribution of texture and red-edge band for vegetated areas detection and identification." In Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International, IEEE, 2013 pp. 4102-4105.
  7. Acuña, R. G. Gonzalez, Junli Tao, and Reinhard Klette. "Generalization of Otsu's binarization into recursive colour image segmentation." In Image and Vision Computing New Zealand (IVCNZ), 2015 International Conference on, IEEE, 2015 pp 1-6.
  8. S. K. Tichkule and D. H. Gawali. "Plant diseases detection using image processing techniques." In Green Engineering and Technologies (IC-GET), 2016 Online International Conference on, pp. 1-6. IEEE, 2016.
  9. H. Chi, C. Jian, C. Wu, J. Zhu, X. Wang, and C. Liu. "Scaffolding progress monitoring of LNG plant maintenance project using BIM and image processing technologies." In Research and Innovation in Information Systems (ICRIIS), 2017 International Conference on, pp. 1-6. IEEE, 2017.
  10. N. Senthilkumaran, and R. Rajesh. "Edge detection techniques for image segmentation–a survey of soft computing approaches." International journal of recent trends in engineering 1, no. 2 (2009): 250-254.
  11. A. Devbrat, and J. Jha. “A Review on Content Based Image Retrieval Using Feature Extraction ” International Journal of Advanced Research in Computer Science and Software Engineering Volume3, March 2016.
  12. L. H. Thai, T. S. Hai, Nguyen Thanh Thuy . “Image Classification using Support Vector Machine and Artificial Neural Network” International Journal on Information Technology and Computer Science,2012, 5, 32-38.
  13. S. Tharani and L. Sankari. “A Study on Image Segmentation Using Different Types of K-Means Clustering”International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE) Volume 33,December 2015
  14. A. Bala, A. K. Sharma. “Color Image Segmentation Using K-means Clustering and Morphological Edge Detector”International Journal of Latest Trend in Engineering and Technology. ISSN: 2278-621, 2016
  15. K. Sumithra, S. Buvana, R. Somasundaram. "A Survey on Various Types of Image Processing Technique" International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, Vol. 4, March-2015
  16. P. Gupta, "A Survey Of Techniques And Applications For Real Time Image Processing." Journal of Global Research in Computer Science (UGC Approved Journal) 4, no. 8 (2013): 30-39
  17. G. B. Souza, G. M. Alves, A. LM Levada, P. E. Cruvinel, and A. N. Marana. "A Graph-Based Approach for Contextual Image Segmentation" In Graphics, Patterns and Images (SIBGRAPI), 2016 29th SIBGRAPI Conference on,. IEEE 2016, pp. 281-288