A Fast Feature Matching Algorithm Based on Multi Scale Spatial Segmentation Technology

SIFT (Scale invariant feature transform) and correlative algorithms are now widely used in content based image retrieval technology. They compute distance and use neighbor algorithm to look for the optimal matching couples. The disadvantage of such way is high complexity, especially when huge amount of images need to be retrieved or recognized. To solve this problem, a new matching way based on feature space division under multi-scale is proposed. The algorithm will divide the feature space under multiple scales, so that those feature points which are located in somewhere can use a code to represent, and finally realize the matching through the code. Without calculating distance, the algorithm complexity is greatly reduced. Experiments show that, the algorithm keeps the matching accuracy and greatly enhance the efficiency of the matching at the same time.