There are many researches on cementing implementation methods and engineering detection methods of cementing quality, but the analysis of picture results on cementing quality is relatively rare. In this paper, a text coordinate position reference algorithm for focusing image analysis range and an image analysis algorithm based on histogram similarity and gradient distance are proposed to evaluate cement quality using evaluation image. A combination of image analysis algorithm and business mechanism is used to extract quantitative data from the evaluation image to evaluate cementing quality. Through comparison of model experiments, the proposed image analysis algorithm can accurately identify the cement quality information in the picture, and the error rate between the analytic results and the actual results is less than 10%. The method proposed in this paper can effectively solve the shortcomings of low efficiency and large error of manual analysis, and provides a practical solution to the situation that electronic data of cementing quality is missing and only the cementing quality evaluation image is kept. The proposed algorithm has strong exploratory significance for deep mining of cementing quality pictures.