Study On The Key Technology Of Automatic Calibration Of Hand-held Laser Rangefinder

The hand-held laser rangefinder(hereinafter referred to as the rangefinder)is an instrument that uses laser to accurately measure the distance of the target.In recent years,rangefinder has been widely used in engineering industry because of its small size,light weight,fast and accurate measurement.In order to ensure the accuracy of the indication of the rangefinder,it is necessary to calibrate the rangefinder regularly.At present,most of the rangefinders have no communication interface and need to read the indication of the rangefinder manually.However,with the rapid increase of the number of tested instruments,the workload of manual calibration is large,so it is of great significance and application value to develop a set of automatic calibration device of the rangefinder.In view of the problems of the possibility and low efficiency of the error caused by human factors in the calibration of rangefinders,the digital recognition technology is applied to the measurement and calibration of rangefinders.Based on the existing calibration system of the Chinese Academy of metrology,a set of automatic calibration device for rangefinders is developed.The main work of this paper is as follows:1.Design of hardware device for automatic calibration of rangefinderIn view of the problems such as many kinds and different volumes of rangefinders,it is difficult to ensure that the rangefinders are perpendicular to the back datum plane,the bottom surface is not smooth,and the laser beam cannot be parallel to the measuring direction of the calibration platform,which leads to the inability to shoot to the target plate.Combined with the characteristics of the rangefinders and the actual calibration requirements,a multi degree of freedom adjustable clamping device is designed to realize the flexible adjustment of the position of the rangefinders.2.Algorithm research of image preprocessingFirstly,the display image of the rangefinder is acquired by the image acquisition system,then the character target area is intercepted,and then the character target area is preprocessed.Finally,the image after preprocessing is segmented by the principle of projection method,which lays the foundation for subsequent analysis.3.Research on image recognition algorithmThree methods of fingerprint recognition,which are based on Tesseract engine and BP neural network,are studied and analyzed.In fingerprint recognition algorithm,the recognition rate of template one,template two and template fingerprint database matching is 59%,75% and 99% respectively.In the study of Tesseract recognition,the recognition rate of the preprocessed image is 20% higher than that of the original image.In the study of BP neural network recognition,100,1000 and 3000 pictures are used as training sets,and 50,500 and 1000 pictures are used as verification sets.The recognition rates are 78%,93.7% and 99.4% respectively.Then the comparison experiments of three algorithms are carried out.Through the analysis and summary of experiments,the recognition rate of BP neural network is the highest,the recognition rate is 90%.