This paper presents the classification method of various paddy varieties as per the rice processing requirement. In first phase four morphological features of the individual as well as group's average features of paddy were extracted using image processing. Out of these four features only two features (minor axis and area) are providing sufficient information to classify the paddy as per the requirement of rice dryer and processing plant. In the second stage a feed forward neural network was applied to classify the extracted data. These data were classified in to large, medium and small samples. Another 10 sets of samples were tested using NN and it is found that all these samples are classified properly.

1. B. S. Anami ,D.G.Savakar: 2009 Improved method for identification and classification of foreign bodies mixed food grains image samples,ICGST-AIML Journal,vol.9,isssue1.
2. E. Barati,J. A. Esfahani:- 2011 Mathematical modelling of convective drying :Lumped temperature and spatially distributed moisture in slab, Elsevier Energy 36(2011),2294-2301.
3. Somkiat Prachayawarakorn et. al.:2005 Journal of stored products research, 41(2005), 333-351.
4. Liu –yen, Cheng Fang, Ying Yi –bin, and Rao Xin-qin: 2005 Identification of rice seed varieties using neural network,Journal of Zhejiang uni.Science, 6b(11):1095-1100.
5. I.Zayas ,Y.Pomeranz ,and F.S.Lai: Discrimination of Wheat seed and nonwheat components in Grain samples by image analysis, vol.66,No. 3,1989 .
6. N.S. Visen ,J.Paliwal ,D.S.Jayas and N.D.G.White: 2004 Image analysis of bulk grain samples using neural networks,canadian biosystem engg.vol.46.
7. I. Y. Zayas ,C.R.Martine, J.L.Steele,A.Ketsevich: 1996 Wheat classification using image analysis and crush force parameters ,American society of Agricultural Engineers 1996,vol.39(6):2199-2204.
8. P.H.Gramitto ,H.D.Navone,P.F.Verdes ,and H.A.Caccatto : Automatic identification of weed seeds by colour image processing
9. Ali Douik and Mehrez Abdellaoui : 2008 Cereal varieties classification using wavelet techniques combined to multi-layer neural networks,16th Mediterranean conference on control and automation, Congress centre Ajaccio France, June 25-27
10. Jitendra N. Chourasia and Preeti Bajaj:- 2011 Centroid Based Detection Algorithm for Hybrid Traffic Sign Recognition System, proceedings of ICETET pg. 96

Grain samples Machine vision Neural network Paddy varieties Classification