Identification of apple leaf varieties using image processing and adaptive neuro- fuzzy inference system

Document Type : Research Paper

Authors

1 graguated of Biosystem Engineering, University College of Agriculture and Natural Resources, University Of Tehran

2 professor of Biosystem Engineering, University College of Agriculture and Natural Resources, University Of Tehran,

3 professor of Biosystem Engineering, University College of Agriculture and Natural Resources, University Of Tehran

4 Assistant of Biosystem Engineering, University College of Agriculture and Natural Resources, University Of Tehran

Abstract

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.

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References

 
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History

  • Receive Date: 31 December 2013
  • Revise Date: 26 August 2014
  • Accept Date: 24 January 2015

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