Research And Development Of Rice And Wheat Growing Analysis System Based On Digital Image

Rice and wheat are the major food crops in the world,instant and accurate access to information of rice and wheat growing is critical.It is convenient for the managers to make regulatory decisions on the production,pest control,fertilization and so on in timely.In the detection of the growth status of rice and wheat,plant height,coverage,relative chlorophyll contents of leaves and leaf area index are the basic growth indexes of rice and wheat.Their acquisition rely on the artificial experience observation,manual measurement,the method is simple and feasible,but it is subjective;quantitative analysis of indoor chemical,require destructive sampling and poor timeliness;in recent years,spectrum detection as new technology has gradually become a key technical support for object recognition,because of its convenient and efficient nondestructive measurement method,but it still faces the problem of high measuring cost,It is not conducive to promoting.With the rapid development of image sensor and the high-speed processor,the popularity of digital image processing technology is gradually infiltrated into the agricultural information acquisition in the field,mainly used for the prediction of crop yield,insect pest detection,weed identification,crop nutrition monitoring,quality inspection,measurement and other aspects of plant morphology.This study adopts digital image processing technology research and development of rice and wheat growing digital image analysis system,the system can realize image acquisition and processing of rice and wheat image,feature extraction and agronomic parameters interpretation and other functions,can detect in rice and wheat plant height,coverage,relative chlorophyll contents of leaves,leaf area index.The main research contents and results are as follows:1.Digital image acquisition and processing of rice and wheat growth;Select the CMOS image acquisition module according to the application demand,and comparative analysis of current communication mode and intelligent terminal equipment performance,to integrate rice and wheat growing digital image acquisition CMOS-Ethernet-PC platform hardware modole,it can collect the canopy top view,side view image.Comparative and analysis the results of each image processing algorithm,to selecte image processing scheme:contrast image enhancement(each channel histogram)results,according to the Shuangfeng principles,selecte 2*G-R-B channel of top view image and G-R channel of side view image;contrast image segmentation(Otsu method,iterative method,maximum entropy method,Sobel edge detection method,Laplacian edge detection method and Canny edge detection method),according to the supervised evaluation,selecte Otsu method;contrast image restoration(median filtering,mean filtering,Wiener filtering)results,according to the peak signal-to-noise ratio,selecte median filtering method.Extract color feature value(average color feature value,the ratio of color difference color characteristic value,characteristic value,normalized difference color feature value,normalized color characteristic value,comprehensive color feature value),extract texture feature value,extract shape feature value.Provide data basis for the next modeling.2.Model construction of digital image analysis system for rice and wheat growth;The canopy coverage,relative chlorophyll contents of leaves and leaf area index were measured by Photoshop software,SPAD-502 chlorophyll analyzer and LAI-2200C canopy analyzer respectively.the plant height were measured by tape.Analyze the correlation between the extracted image features and agronomic parameters.The regression model is established by the high correlation image feature values.According to the correlation coefficient,the coefficient of determination,root mean square error and relative error,determine the degree of correlation with the image characteristic value of rice and wheat agronomic parameters and the prediction accuracy of the model.Finally,the estimated model of image plant height and real plant height was y=1.057x-2.769,R2 was 0.856,RMSE was 5.794,and the R2 of prediction plant height and actual plant height was 0.706,RMSE was 0.374;The estimated model of image coverage and the coverage obtained by Photoshop software was y=0.911x+0.030,R2 was 0.753,RMSE was 0.054,and the R2 of prediction coverage and the actual coverage was 0.939,RMSE was 0.031;The correlation coefficient of the color feature g and relative chlorophyll contents of leaves was 0.916,and the estimated model was y=34.467x+27.035,R2 was 0.839,RMSE was 1.541;The R2 of prediction relative chlorophyll contents of leaves and the actual SPAD value was 0.697,RMSE was 2.909;The correlation coefficient of the color feature G-B and leaf area index measured by LAI-2200C was 0.803,and the estimated model was y=0.279e0.038x,R2 was 0.833,RMSE was 0.64;The R2 of prediction leaf area index and the actual leaf area index was 0.790,RMSE was 0.158;3.Research and development of the application software of rice and wheat growth digital image analysis system;Based on the Windows platform,the c/s image analysis system of rice and wheat growth was designed and realized by using the GUI function of Matlab software.The main features include image reading(JPEG file)and display,image processing(image channel extraction,six kinds of image segmentation,three kinds of image restoration)and the results display,the image feature extraction(color feature value,texture feature value and morphological characteristics value)and data display,image interpretation(rice and wheat plant height,coverage degree,relative chlorophyll contents of leaves,leaf area index)of the image data and display the result,empty reset.The results show that the design of digital image analysis system for rice and wheat growth is easy to operate and has good interaction.The estimation methods of plant height,coverage,relative chlorophyll contents of leaves and leaf area index were successfully explored.The established estimation model is practical.