Rice disease recognition method based on principal component analysis and neural network and rice disease recognition system thereof

Abstract

The invention relates to a rice disease recognition method based on principal component analysis and a neural network. The method comprises the steps that rice disease image data are acquired and image preprocessing is performed; visual saliency detection is performed, and rice disease images of ideal disease spot outlines are searched from salient map sequences; features are extracted from the rice disease images from the aspects of color, shape and texture, and difference analysis and principal component analysis are performed so that different feature combinations are found; and construction of a machine learning model is performed on different feature combinations and a prediction result is fed back to a client side. The invention also discloses a rice disease recognition system based on principal component analysis and the neural network. Image information is acquired and the images are transmitted to a server side through the network. Preprocessing and disease spot detection are performed on the acquired tissue culturing images through the server side, and management personnel are prompted through a mobile phone short message and a signal lamp and a PC side according to the detection result.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a rice disease recognition method and system based on principal component analysis and neural network. Background technique [0002] Image recognition technology has been applied in various fields. At present, the relatively mature ones include fingerprint recognition, face recognition and intelligent transportation. It is also reflected in intelligent agriculture, map and terrain registration, natural resource analysis, weather forecast, environmental monitoring and physiological pathology research. and many other fields. In agriculture, such as the detection of crop diseases and insect pests, it is possible to detect the disease and insect pests and growth conditions of crops through image recognition technology. [0003] At present, most of the image recognition technologies used in agriculture are researched and processed for some crops that grow naturally, and the...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the image recognition technologies used in agriculture are researched and processed for some crops that grow naturally, and there is no specific pest detection system for rice. Most of them rely on manual detection of pests and diseases, lacking intelligence and automation.

Due to the low accuracy rate of rice disease identification or the large dimensionality, the trade-off between the two brings a certain cost to the development of rice disease identification system

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