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Analysis of Rice Granules using Image Processing and Neural Network Pattern Recognition Tool

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 7
Year of Publication: 2014
Abirami. S
Neelamegam. P
Kala. H.

Abirami. S, Neelamegam. P and Kala. H.. Article: Analysis of Rice Granules using Image Processing and Neural Network Pattern Recognition Tool. International Journal of Computer Applications 96(7):20-24, June 2014. Full text available. BibTeX

	author = {Abirami. S and Neelamegam. P and Kala. H.},
	title = {Article: Analysis of Rice Granules using Image Processing and Neural Network Pattern Recognition Tool},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {7},
	pages = {20-24},
	month = {June},
	note = {Full text available}


In foodstuff trade, grading of coarse food resources is essential because samples of stuffs are subjected to adulteration. In the precedent, foodstuffs in the appearance of granules were conceded through sieves or supplementary mechanical way for grading purposes. In this manuscript, investigation is performed on basmati rice granules; to appraise the act via image processing and Neural Network Pattern Recognition Tool which is implemented based on the features extracted from rice granules for categorization grades of granules. Digital imaging is acknowledged as a proficient system, to haul out the features from rice granules in a non-contact mode. Images are acquired for rice using camera. Image Pre-processing techniques, Adaptive thresholding, Canny edge detection, Feature extraction are the checks that are performed on the acquired image using image processing method through Open source Computer Vision (Open CV) which is a library of functions that aids image processing in real time. The morphological features extracted from the image are given to Neural Network Pattern Recognition Tool. This effort has been prepared to categorize the appropriate quality category for a specified rice sample based on its parameters. The performance of image processing condensed the time of action and enhanced the crop identification significantly.


  • B. S. Anami, V. Burkpalli, S. A. Angadi, and N. M. Patil, "Neural network approach for grain classification and gradation," Proceedings of the second national conference on document analysis and recognition, pp. 394-408, July 2003.
  • N. S. Visen, J. Paliwal, D. S. Jayas, and N. D. G. White, "Image analysis of bulk grain samples using neural networks," Canadian Biosystems Engineering, vol. 46, pp. 7. 11-7. 18, 2004.
  • R. M. Haralick, K. Shanmugam, and I. Dinstein, "Texture features for image classification," IEEE Trans. on Syst. ,Man, and cybern, vol 6, pp. 610-621, 1973.
  • L. Zhao yan, C. Fang, Y. Yibin, and R. Xiuqin, "Identification of rice seed varieties using neural network", Journal of Zhejiang University SCIENCE, September 2005.
  • M. A. Shahin and S. J. Symons, "Seed sizing from images of non-singulated grain samples", Can. BioSyst. Eng, vol. 47, 2005.
  • J. Paliwal, M. S. Borhan and D. S. Jayas, "Classification of cereal grains using a flatbed scanner", Can Biosyst Eng, vol. 46, 2004.
  • Sanjivani Shantaiya, Mrs. Uzma Ansari, "Identification Of Food Grains And Its Quality Using Pattern Classification," International Journal of Computer & Communication Technology, vol 2, 2010.
  • H. Rautio and O. Silvn, "Average Grain Size Determination using Mathematical Morphology and Texture Analysis".
  • S. Deena Christilda, M. Prathiba, and P. Neelamegam , " Quality Inspection of Parenteral Vials Using Digital Image Analysis," Sensors & Transducers Journal, Vol. 145, Issue 10, pp. 130-137, October 2012.
  • R. Deepak Prasanna, P. Neelamegam, S. Sriram, Nagarajan Raju, "Enhancement of vein patterns in hand image for biometric and biomedical application using various image enhancement techniques," Procedia Engineering, vol. 38, 1174 – 1185, 2012.
  • Sonka, M, Hlavac, V, Boyle, R. , "Image Processing, Analysis, and Machine Vision", PWS publishing, California, USA, 1999.
  • D. W. Sun, "Inspecting pizza topping percentage and distribution by a computer vision method," Journal of Food Engineering, vol. 44, pp 245–249, 2000.
  • Neelamegam. P, Abirami. S, Vishnu Priya. K, Rubalya Valantina. S. , "Analysis of rice granules using Image Processing and Neural Network", in IEEE Conference on Information and Communication Technologies (IEEE), ISBN No. 978-1-4673-5759-3, pp. 879-884, 2013.