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Identification Method of Sunflower Leaf Disease Based on SIFT Point

Jun Liu, Fang Lv, and Bobo Liu
Inner Mongolia University of Technology, Hohhot, China

Abstract—China is the largest country in the world for planting sunflower, and sunflower is an important cash crop in Chinese agriculture. Sunflower diseases are becoming more and more serious, accurate identification and effective control of sunflower diseases are very important for local economic development in China. Traditionally, sunflower disease identification is mainly based on the eye recognition method, which has great limitations and this way is difficult to meet the development needs of modern agriculture. In recent years, with the rapid development of digital image processing technology and computer technology, it provides a new platform for development of sunflower disease identification system. This paper proposes a sunflower leaf disease identification method based on SIFT points mainly for sunflower leaf diseases. In-depth study was conducted on sunflower black spot, bacterial leaf spot, powdery mildew and downy mildew.

Index Terms—digital image processing, SIFT, sunflower leaf disease, identification

Cite: Jun Liu, Fang Lv, and Bobo Liu, "Identification Method of Sunflower Leaf Disease Based on SIFT Point," Journal of Image and Graphics, Vol. 7, No. 2, pp. 64-67, June 2019. doi: 10.18178/joig.7.2.64-67

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