Optical Lens Resolution Detection System Based On Energy Concentration

In recent years,with the development of Artificial Intelligence and automatic industrials,machine vision and AI play an increasing important role in the field of non-contact measurement detection.Optical lens,as the first step of information collection,its resolution will be crucial for the accuracy of information acquisition.However,besides clarity,the quality of optical lens resolution is also associated with distortion,spherical aberration and coma aberration factors.In order to achieve the purpose of detecting optical lens resolution,we must have tests on all possible aberration factors discussed above separately.The state of art methods used for the detection of optical lens' resolution can be divided into two categories:visual inspection method and the optical transfer function method.The shortcoming of these two kinds of methods lies in the error of subjective observations since experimental staff need to differentiate the resolution of optical lens with eyes.In this thesis,we propose a lens resolution detection system based on capability concentration,which aims at high efficiency and accuracy.The system can detect the optical lens through energy concentration as well' as calculate the image aberration according to the energy distribution characteristics.The resolution detection algorithm extract the energy distribution of the lens based on identification rate image.Then the obtained energy information can be used to calculate the concentration value between black and white lines.The third step is to compute the differentiate condition according to different unit block method and the calibration method.Finally,the value of energy concentration and resolution formula are used to calculate the resolution of the optical lens.Among various resolution conditions and aberration factors,the test results show that this algorithm can detect the resolution of optical lens with high accuracy and validity.