Improved feature extraction and matching algorithm for point-line fusion

Aiming at the problems that the feature points extracted by traditional SLAM algorithms are very easy to pile up in texture-rich areas, and the correct rate and speed of feature point matching cannot meet the needs of real-time construction of scene maps, we design a point and line feature fusion as well as an extraction and matching algorithm based on mesh motion statistics. Firstly, the accuracy of line feature extraction is improved by improving the parameters of the line feature extraction algorithm, and then the uniformity of the distribution of feature points is improved by using the grid division during point feature extraction, and then the grid motion statistics algorithm is introduced to eliminate the false matches by counting the distinguishable degree of matching neighborhoods on the basis of the constraints of motion smoothness. Comparing the number of feature points extracted, time consumption, distribution and matching effect, the improved algorithm is able to extract a sufficient number of feature points with uniform distribution, which makes the most use of the useful information of the image; in addition, compared with other similar algorithms, the number of matching pairs is greatly increased while the correct rate is also significantly improved, which in turn verifies the superiority of the improved algorithm.