Research on Color and Shape Recognition of Maize Diseases Based on HSV and OTSU Method

  • Guifen ChenEmail author
  • Ying Meng
  • Jian Lu
  • Dongxue Wang
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 509)


With the application of IOT technology in maize disease images for monitoring and collecting, timely detection of the types and characteristics of identification of disease has become a hot research in the diagnosis and treatment of diseases and insect pests. In order to improve the recognition accuracy of maize leaf, achieve rapid diagnostic purposes, this paper takes the leaf spot of maize gray leaf spot and image as the research object, use the computer image processing technology is studied on the effective segmentation and recognition of color and shape features. The genetic algorithm was adopted to optimize the selection of maize disease images real-time filtering; \( 3 * 3 \) mode noise suppression of the image selected by value smoothing; then select the HSV component of the color feature extraction of the disease; the maximum between class variance (OTSU) disease shape character segmentation and recognition. The results show that, based on genetic algorithm optimization based on image In HSV and Otsu method can be more accurate segmentation and recognition of the disease of color and shape features, and enhance the real-time and accuracy of the image of maize disease detection and recognition and oriented under the condition of things plant diseases and insect pests of maize and provide technical support.


Maize diseases Genetic algorithm Internet of things HSV OTSU 



This work was funded by the China Spark Program. 2015GA66004. “Integration and demonstration of corn precise operation technology based on Internet of things”.


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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.School of Information TechnologyJilin Agricultural UniversityChangchunChina

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