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In order to meet the requirements of real time and saving resources for the visual odometer in driverless cars, a method combining Harris and SIFT by taking advantage of their respective features is proposed. First, Harris operator is used to detect corner points which were regarded as the candidate feature points of an image. And then SIFT algorithm is used to extract features from those corners. Finally, Random Sample Consensus (RANSAC) is used to remove the wrong matching points. Results show that the proposed method has reduced the number of features to be detected, made the algorithm simpler and extracted features faster while good matching efficiency is maintained.

Research on Property of Image Matching Method Based on the Deep Fusion of Harris and SIFT