To solve the problem that the on-line detection of shape and position tolerance of parts in precision machining industry is not real-time and can not detect multiple parts at the same time, the image preprocessing process and measurement method of images collected by camera are improved by using machine vision technology, and an improved non-contact measurement algorithm based on CNN super-resolution reconstruction is proposed. Compared with other super-resolution reconstruction algorithms, the algorithm has the advantages of simple model, high precision and fast speed. It can take into account the measurement accuracy and efficiency under the condition of limited resources. In order to verify the reliability of the designed algorithm, a non-contact measurement system based on machine vision is designed. The experimental results show that the accuracy of the improved measurement method can be improved by at least 47.86% and 49.67% on average compared with the previous measurement method. The super-resolution algorithm on the basis of the resolution must, to the original acquisition of image super-resolution reconstruction after improve image resolution, measurement accuracy is increased by 60.38%, do not use the super-resolution reconstruction using the algorithm for multiple targets online synchronous measurement analysis, and the precision is not lower than with single parts under resolution precision.