Research On Key Technologies Of Remote Measurement System Of Corn Plant Height

With the continuous improvement of science and technology,the continuous deepening of computer application has promoted the rapid development of image processing technology.In order to study the value of image processing in crop growth monitoring,corn is taken as the research object in this paper.The corn plant samples are collected by remote control camera,the corn plant height data was obtained by the corn height measurement system using color image segmentation algorithm to obtain the corn growth potential information.The image processing method is used to measure the height of corn,which provides an efficient and convenient method for measuring the height of corn,effectively reduces the time of manual round trip,improves the efficiency and saves the cost.At the same time,the growth height can reflect the growth status of crops,which has important guiding significance for the crop field management.This paper mainly studies the following contents:Firstly,it is the corn image preprocessing.In the process of corn sample collection,due to the interference of sample collection equipment,environment and other factors,the information contained in the collected sample image is more complex,and it is difficult to accurately segment and extract the corn image.Therefore,first of all,the image is preprocessed,and the corn image is segmented by OTSU combined with color space coordinate transformation algorithm,and an image segmentation method based on improved color algorithm is proposed through comparative analysis.Then,the corn image was processed by morphological processing and hole filling,and the 8-connected components labeling algorithm was used to extract the features of crop target region,which realized the accurate segmentation of corn image and the extraction of target region features.Secondly,it is camera calibration.In order to determine the projection transformation relationship among the corresponding pixel points in the corn image and each coordinate system of the camera imaging model,it is necessary to construct the projection geometric model by using camera parameters.In order to adapt to the lens characteristics of the camera,the improved Zhang Zhengyou calibration method is adopted,and a camera calibration model with nonlinear distortion is introduced to calibrate the camera,so as to achieve distortion correction and obtain the internal parameters of the camera to ensure the shooting accuracy of the acquisition equipment.Thirdly,it is corn plant height measurement.After segmentation and extraction,the corn image was marked with a ruler and a rectangular box of corn plants.The area of the marked rectangle and the coordinates of the rectangular box were obtained by measure the image region property function.And the corresponding ruler height and the average plant height of corn in the image were calculated by using the 8-connected components labeling algorithm.Then,the actual height of corn plant was calculated according to the principle of camera imaging,and the results of plant height measurement in different growth stages of corn under farmland background were compared and analyzed.Combined with the data of corn plant height measured manually,the results show that the corn plant height measurement system based on color space algorithm is feasible,which can effectively improve the accuracy and efficiency of crop height measurement.