2019
DOI: 10.1007/978-3-030-06155-5_30
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Research on Color and Shape Recognition of Maize Diseases Based on HSV and OTSU Method

Abstract: 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 effectiv… Show more

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Cited by 2 publications
(1 citation statement)
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“…In the early stages of conventional machine learning, some scholars used image processing techniques to simply process maize seed images for recognition. Chen et al [6] proposed a method based on image In HSV and Otsu method based on genetic algorithm optimization, which achieved more accurate segmentation and recognition of the disease of color and shape features, and enhanced the real-time and accuracy of the image of maize disease detection and recognition. Subsequently, many researchers began to use neural network approaches for maize seed image analysis.…”
Section: Introuductionmentioning
confidence: 99%
“…In the early stages of conventional machine learning, some scholars used image processing techniques to simply process maize seed images for recognition. Chen et al [6] proposed a method based on image In HSV and Otsu method based on genetic algorithm optimization, which achieved more accurate segmentation and recognition of the disease of color and shape features, and enhanced the real-time and accuracy of the image of maize disease detection and recognition. Subsequently, many researchers began to use neural network approaches for maize seed image analysis.…”
Section: Introuductionmentioning
confidence: 99%