Identification of Canola Seeds using Nearest Neighbor and K-Nearest Neighbor Algorithms

作者: Altaf Saeed , Muhammad Tariq , Muhammad Ibrahim , Nazir Ahmad , Abu Mazhar Ahmad

DOI:

关键词:

摘要: Agriculture plays an important role on Pakistan economy. Canola is the major crop of Pakistan. There are different varieties canola crop. It fulfills requirement oil. difficult task to identify best seeds for sowing due seeds. In this paper we try introduce machine learning approaches classification which provide opportunity people or farmer verities implementing by computer vision image processing tool. We have 4 names as Gobhi Sarson (A), Barassica comp (B), Sathri (C) and Rocket Herbof (D) take images from these varieties. Each variety has 10 total 10*4 =40 train test data results all kinds then will be compare pattern apply nearest neighbor k-nearest algorithms final in achieved 85% 76% average 90% 73% a results. These percentage more accuracy. other Keywords:  Features, Pattern classification, neighbor,

参考文章(21)
M.A. Shahin And S.J. Symons, Lentil type identification using machine vision ,(2003)
Pablo Miguel Granitto, Hugo Daniel Navone, Pablo Fabián Verdes, Hermenegildo Alejandro Ceccatto, None, Automatic identification of weed seeds by color image processing VI Congreso Argentino de Ciencias de la Computación. ,(2000)
Zhao-yan Liu, Fang Cheng, Yi-bin Ying, Xiu-qin Rao, Identification of rice seed varieties using neural network. Journal of Zhejiang University-science B. ,vol. 6, pp. 1095- 1100 ,(2005) , 10.1631/JZUS.2005.B1095
Guiping Liao, Jinwei Li, Xiaojuan Yu, Zhao Tong, Plumpness Recognition and Quantification of Rapeseeds using Computer Vision Journal of Software. ,vol. 5, pp. 1038- 1047 ,(2010) , 10.4304/JSW.5.9.1038-1047
A. Nasirahmadi, N. Behroozi-Khazaei, Identification of bean varieties according to color features using artificial neural network Spanish Journal of Agricultural Research. ,vol. 11, pp. 670- 677 ,(2013) , 10.5424/SJAR/2013113-3942
Ouiza Adjemout, Kamal Hammouche, Moussa Diaf, Automatic seeds recognition by size, form and texture features information sciences, signal processing and their applications. pp. 1- 4 ,(2007) , 10.1109/ISSPA.2007.4555428
Hasan Yalcin, Omer Said Toker, Ismet Ozturk, Mahmut Dogan, Ozgur Kisi, Prediction of fatty acid composition of vegetable oils based on rheological measurements using nonlinear models European Journal of Lipid Science and Technology. ,vol. 114, pp. 1217- 1224 ,(2012) , 10.1002/EJLT.201200040
Xiao Chen, Yi Xun, Wei Li, Junxiong Zhang, None, Combining discriminant analysis and neural networks for corn variety identification Computers and Electronics in Agriculture. ,vol. 71, ,(2010) , 10.1016/J.COMPAG.2009.09.003
N. Wang, F. E. Dowell, N. Zhang, Determining wheat vitreousness using image processing and a neural network Transactions of the ASABE. ,vol. 46, pp. 1143- 1150 ,(2003) , 10.13031/2013.13937
Salah Ghamari, Classification of chickpea seeds using supervised and unsupervised artificial neural networks African Journal of Agricultural Research. ,vol. 7, pp. 3193- 3201 ,(2012) , 10.5897/AJAR11.2071