A Two-Person Lift Image Detail Extraction Method based on Global Texture Feature Optimization

摘要

When traditional information extraction methods are used to extract image feature points, image denoising degree is not sufficient, and there are still small scale noise points in detail images, which leads to the spatial dimension error of information extraction. To solve this problem, a new method based on global optimization texture feature is proposed to extract the details of double lift image. Using laser scanning measurement technology, the data of double lift image is collected, the point cloud data of image is preprocessed, and the detail feature points are extracted. The texture sequence of feature points is obtained by using the global optimization texture feature technology, and the detail color and texture are mapped into the grid to obtain the detail information of the lifting image. The experimental results show that the spatial dimension error of this method is smaller than that of the two traditional methods, which makes the extracted information meet the requirements of high precision and increase the reliability of information extraction.