Mehran University Research Journal Of Engineering &
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Publishing Since 1982.

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Classification of Broken Rice Kernels using 12D Features

Keywords: Rice Classification, Feature Extraction, Image Analysis, Hough Transform, Radial Basis Function.

Mehran University Research Journal of Engineering & Technology

Volume 35 ,  Issue 3


1. Abdullah, M.Z., Fathinul-Syahir, A.S., and Mohd-Azemi, B.M.N., "Automated Inspection System for Color and Shape Grading of Starfruit (Averrhoa Carambola L.) Using Machine Vision Sensor", Transactions of the Institute of Measurement and Control, Volume 27, No. 2, pp. 65-87, 2005
2. Louise, F., "Rice is Life", Journal of Food Composition and Analysis, Volume 18, No. 4, pp. 249-253, 2005.
3. Kruthika, R., Muruganand, S., and Periasamy, A., "Matching of Different Rice Grains using Digital Image Processing", International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Volume 2, No. 7, pp. 2937-2941, 2013.
4. Verma, B., "Image Processing Techniques for Grading and Classification of Rice", International Conference on Computer Communication and Technology, pp. 220-223, 2010
5. Moreda, J.P., Ortiz-Canavate, J., Garcia-Ramos, F.J., and Ruiz-Altisent, M., "Non-Destructive Technology for Fruit and Vegetable Size Determination – A Review", Elsevier Journal of Food Engineering, Volume 92, No. 2, pp. 119-136, 2009.
6. Dalen, G.V., "Determination of the Size Distribution and Percentage of Broken Kernels of Rice Using Flatbed Scanning and Image Analysis", Elsevier Food Research International, Volume 37, No.1, pp. 51-58, 2004.
7. Yadav, B.K., and Jindal, V.K., "Modeling Changes in Milled Rice (Oryza Sativa L.) Kernel Dimensions during Soaking by Image Analysis", Elsevier Journal of Food Engineering, Volume 80, No. 1, pp. 359-369, 2007
8. Rad, S.J.M., Tab, F.A., and Mollazade, K., "Classification of Rice Varieties using Optimal Color and Texture Features and BP Neural Networks", 7th Iranian Conference on Machine Vision and Image Processing, pp. 1-5, 2011.
9. Ding, K., and Gunasekaran, S., "Shape Feature Extraction and Classification of Food Material using Computer Vision", Transactions of the American Society of Agriculture Engineers, Volume 37, No. 5, pp. 1537-1545, 1994
10. Uddin, M.Z., Lee, J.J., and Kim, T. S., "An Enhanced Independent Component Based Human Facial Expression Recognition from Video", IEEE Transactions on Consumer Electronics, Volume 55, No. 4, pp. 2216-2224, November, 2009.
11. Schels, M., and Schwenker, F., "A Multiple Classifier system Approach for Facial Expressions in Image Sequences utilizing GMM Super Vectors", Proceedings of 20th International Conference on Pattern Recognition, pp. 4251-4254, August, 2010.
12. Kaur, H., and Singh, B., "Classification and Grading Rice using Muti-Class SVM", International Journal of Scientific and Research Publications, Volume 3, No. 4,pp. 1-5, 2013.
13. Kumar, S., and Hebert, M., "Discriminative Fields for Modeling Spatial Dependencies in Natural Images",Advances in Neural Information Processing Systems,Volume 16, MIT Press, Cambridge, USA, 2003
14. Liu, Z.Y., Cheng, F., Ying, Y.B., and Rao, X.Q., "Identification of Rice Seed Varieties using Neural Network", Journal of Zhejiang University Science-B,Volume 6, No. 11, pp. 1095-1100, 2005
15. Marin, D., Aquino, A., Gegundez-Arias, M.E., and Bravo, J.M., "A New Supervised method for Blood vessel Segmentation in Retinal Images by using Gray-Level and Moment-Invariants Based Features", IEEE Transactions on Medical Imaging, Volume 30, No. 1, pp. 146-158, 2010
16. Zhang, Q., Yeo, T.S., Tan, H.S., and Luo, Y., "Imaging of a Moving Target with Rotating Parts Based on the Hough Transform", IEEE Transactions on Geoscience and Remote Sensing, Volume 46, No. 1, pp. 291-299, 2008
17. Khowaja, S.A., Shah, S.M. Z.S., and Memon, M.U., "Noise Reduction Technique using Radial Basis Function Neural Networks", Volume 33, No. 3, pp. 278-285, 2014
18. Bai, X., Zhou, F., and Jin, T., "Enhancement of Dim Small Target through Modified Top Hat Transformation under the Condition of Heavy Clutter", Elsevier Signal Processing, Volume 90, No. 5, pp. 1643-1654, 2010.
19. Sapirstein, H.D., Neuman, M., Wright, E.H., Shwedyk, E., and Bushuk, W., "An Instrumental System for Cereal Grain Classification using Digital image Analysis", Elsevier Journal of Cereal Science, Volume 6, No. 1, pp. 3-14, 1987.
20. Zayas, I., Pomeranz, Y., and Lai, F.S., "Discrimination of Wheat and Non-Wheat Components in Grain Samples by Image Analysis", Cereal Chemistry, Volume 66, No. 3, pp. 233-237, 1989.
21. Zayas, I.Y., Martin, C.R., Steele, J.L., and Katsevich, A., "Wheat Classification using Image Analysis and Crush- Force Parameters", Transactions of the American Society of Agriculture Engineers, Volume 39, No. 6, pp. 2199-2204, 1996
22. Wee, C.Y., Paramesran, R., Takeda, F., Tsuzuki, T., Kadota, H., and Shimanouchi, S., "Classification of Rice Grains using Fuzzy ARTMAP Neural Network", Asia Pacific Conference on Circuits and Systems, Volume 2,pp. 223-226, 2002
23. Danying, W., Xiufu, Z., Zhiwei, Z., Neng, C., Jie, M., Qing, Y., Jianli, Y., and Xiyuan, L., "Correlation Analysis of Rice Grain Quality Characteristics", Volume 31, No. 8, pp. 1086-1091, 2005.
24. Wee, C.Y., Paramesran, R., and Takeda, F., "Fast Computation of Zernike Moments for Rice Sorting Systems", IEEE International Conference on Image Processing, Volume 6, pp. 165-168, 2007
25. Agustin, O.C., and Byung-Joo, O., "Automatic Milled Rice Quality Analysis", 2nd International Conference on Future Generation Communication and Networking,Volume 2, pp. 112-115, 2008.
26. Pearson, T., "Hardware-Based Image Processing for High Speed Inspection of Grains", Elsevier’s Computers and Electronics in Agriculture, Volume 69, No. 1, pp. 12-18, 2009
27. Pabamalie, L.A.I., and Premaratne, H.L., "A Grain Quality Classification System", International Conference on Information Society, pp. 56-61, 2010.
28. Rad, S.J.M., Tab, F.A., and Mollazade, K., "Design of an Expert System for Rice Kernel Identification using Optimal Morphological Features and Back Propagation Neural Network", International Journal of Applied Information Systems, Volume 3, No. 2, pp. 33-37, 2012.
29. Pazoki, A.R., Farokhi, F., and Pazoki, Z., "Classification of Rice Grain Varieties using Two Artificial Neural Networks (MLP and Neuro-Fuzzy)", The Journal of Animal and Plant Sciences, Volume 24, No. 1, pp. 336-343, 2014.
30. Xu, S., Zhou, Z., Lu, H., Luo. X., and Lan, Y., "Improved Algorithms for the Classification of Rough Rice using a Bionic Electronic Nose Based on PCA and the Wilks Distribution", Sensors, Volume 14, No. 3, pp. 5486-5501, 2014.
31. Abdullah, A.H., Adom, A.H., Shakaff, A.Y.M., Masnan, M.J., Zakaria, A., Rahim, N.A., and Omar, O., "Classification of Malaysia Aromatic Rice using Multivariate Statistical Analysis", International Conference on Mathematical Engineering and Industrial Applications, Volume 1660, pp. 090005, 2015.
32. Wang, L., Liu, D., Pu, H., Sun, D.W., Gao, W., and Xiong, Z., "Use of Hyperspectral Imaging to Discriminate the Variety and Quality of Rice", Food Analytical Methods, Volume 8, No. 2, pp. 515-523, 2015.
33. Zhang, B., Wu, X., You, J., Li, Q., and Karray, F., "Detection of Microaneurysms using Multi-Scale Correlation Coefficients", Elsevier Pattern Recognition Letters, Volume 43, No. 6, pp. 2237-2248, June, 2010
34. FTP Site for Counting Grains of Rice http://", Date accessed: 29/09/2015.
35. Ngampak, D., and Piamsanga, P., "Image Analysis of Broken Rice Grains of Khao Dawk Mali Rice", 7th International Conference on Knowledge and Smart Technology, pp. 115-120, January, 2015
36. Neimeijer, M., Ginneken, V.B., Staal, J.J., Suttorp- Schulten, M.S.A., and Abramoff, M.D., "Automatic Detection of Red Lesions in Digital Color Fundus Photographs", IEEE Transactions on Medical Imaging, Volume 24, No. 5, pp. 584-592, May, 2005.
37. Zhang, B., Wu, X., You, J., Li, Q., and Karray, F., "Detection of Microaneurysms using Multi-Scale Correlation Coefficients", Pattern Recognition Letters, Volume 43, pp. 2237-2248, 2010
38. Jagoe, R., Arnold, J., Blauth, C., Smith, P.L.C., Taylor, K.M., and Wootton, R., "Measurement of Capillary Dropout in Retinal Angiograms by Computerized Image Analysis", Pattern Recognition Letters, Volume 13,pp. 143-151, 1992