University of Tehran Press Iranian Journal of Biosystem Engineering 2008-4803 46 1 2015 03 21 Identification of apple leaf varieties using image processing and adaptive neuro- fuzzy inference system Identification of apple leaf varieties using image processing and adaptive neuro- fuzzy inference system 67 75 54338 10.22059/ijbse.2015.54338 FA Elham Omrani graguated of Biosystem Engineering, University College of Agriculture and Natural Resources, University Of Tehran Seyed Saeid Mohtasebi professor of Biosystem Engineering, University College of Agriculture and Natural Resources, University Of Tehran, 0000-0002-4031-1095 Shahin Rafiee professor of Biosystem Engineering, University College of Agriculture and Natural Resources, University Of Tehran Soleiman Hosseinpour Assistant of Biosystem Engineering, University College of Agriculture and Natural Resources, University Of Tehran Journal Article 2013 12 31 In modern agriculture, image processing technique is used for mechanization and intelligent machines instead of humans. One of them is identifying varieties of plants and fruits. Identifying plant varieties is important in Plant eugenic programs. Visual examination of plant leaves and fruits are the common processes for this aim. Identification and classification of plants using machine vision techniques can be performed more quickly. In this study, four varieties of apple, Granny Smith, Golab Kohans, Gala, and Delbar-astyval were studied. After collecting leaf samples, the images of leaves were captured and then color, texture, and morphological properties from each image were extracted and adaptive neuro - fuzzy inference system (Anfis) was used for classification. The results showed that ANFIS was able to successfully classify leaves with input and output membership functions, respectively, linear and triangular and hybrid learning method in grid partitioning FIS mood with 95.83% accuracy. In modern agriculture, image processing technique is used for mechanization and intelligent machines instead of humans. One of them is identifying varieties of plants and fruits. Identifying plant varieties is important in Plant eugenic programs. Visual examination of plant leaves and fruits are the common processes for this aim. Identification and classification of plants using machine vision techniques can be performed more quickly. In this study, four varieties of apple, Granny Smith, Golab Kohans, Gala, and Delbar-astyval were studied. After collecting leaf samples, the images of leaves were captured and then color, texture, and morphological properties from each image were extracted and adaptive neuro - fuzzy inference system (Anfis) was used for classification. The results showed that ANFIS was able to successfully classify leaves with input and output membership functions, respectively, linear and triangular and hybrid learning method in grid partitioning FIS mood with 95.83% accuracy. https://ijbse.ut.ac.ir/article_54338_cb51c498760b96443a8209926ef42302.pdf