Matching of small packages of traditional Chinese medicine based on improved RANSAC algorithm

Abstract

The vision system model of small package sorting of traditional Chinese medicine was constructed, and the chessboard calibration method was used to calibrate the binocular camera. Surf algorithm and orb algorithm are analyzed by experiments, and orb algorithm with high real-time performance is used to extract feature points. The fast nearest neighbor FLANN algorithm is used to quickly match the feature points, and the matched feature points are screened according to Lowe’s algorithm and v-axis coordinate consistency principle, to solve the problem of false matching points. The method of selecting feature points based on matching quality ranking to calculate the homography matrix is designed, which solves the random sampling problem of the RANSAC algorithm and effectively shortens the time of feature matching.