Leaf Image Classification Using Support Vector Machine

Received: 21-08-2013

Accepted: 29-10-2013

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Issue: Vol. 11 No. 7 (2013)

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KỸ THUẬT VÀ CÔNG NGHỆ

How to Cite:

Hong, P., Ha, D., & Thuy, N. (2024). Leaf Image Classification Using Support Vector Machine. Vietnam Journal of Agricultural Sciences, 11(7), 1045–1052. http://testtapchi.vnua.edu.vn/index.php/vjasvn/article/view/1662

Leaf Image Classification Using Support Vector Machine

Phan Thi Thu Hong (*) 1 , Doan Thi Thu Ha 2 , Nguyen Thi Thuy 2

  • 1 Khoa Công nghệ thông tin, Học viện Nông nghiệp Việt Nam
  • 2 Khoa Công nghệ thông tin,Trường Đại học Nông nghiệp Hà Nội

    • Keywords

    Computer vision, image classification, leaf recognition, support vector machine

    Abstract


    Computer vision is an inter-discipline research field, which has many real life applications. One of the important tasks is to identify and classify objects from their digital images. Computer vision has been applied successfully in many fields of agriculture such as agricultural automation, precision agriculture, classification of agricultural products and identification (trees, weeds, fruits etc). This paper presents the application of the computer vision technique to leaf image classification by using Support Vector Machine (SVM). The experimental results with classification accuracy of 98% showed the success of using SVM to classify leaf images. This also showed that the approach can be employed for other practical applications effectively.

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