›› 2015, Vol. 58 ›› Issue (12): 1338-1343.

• RESEARCH PAPERS • Previous Articles     Next Articles

A method for image segmentation and recognition of spider mites based on K-means clustering algorithm

LIU Guo-Cheng1, ZHANG Yang1, HUANG Jian-Hua2,*, TANG Wen-Liang3   

  1. (1. Guangzhou Railway Polytechnic, Guangzhou 510430, China; 2. Institute of Plant Protection, Jiangxi Academy of Agricultural Sciences, Nanchang 330200, China; 3. School of Software, East China Jiaotong University, Nanchang 330013, China)
  • Online:2015-12-20 Published:2015-12-20

Abstract: 【Aim】 The spider mites are the main pests of many crops. Traditional recognition methods for spider mites relied on the naked eyes, which wasted a lot of time and energy. In order to study the fast automatic recognition method for spider mites, a method using computer image analysis algorithm was developed. 【Methods】 The method based on the K-means clustering algorithm realized the segmentation and recognition of the spider mite images which were obtained from fields. 【Results】 In contrast to the traditional RGB color segmentation method, the K-means clustering algorithm method was able to separate the images of spider mites from leaf background effectively. The average recognition time based on the K-means clustering algorithm was 3.56 s, and the recognition accuracy was 93.95%. The recognition time (T) increased as the pixels of tested image (Pi) increased. 【Conclusion】 The method can be applied to the segmentation and recognition of spider mite images.

Key words: Spider mite, image, K-means algorithm, image segmentation, image recognition, pixels