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As one of the most prominent and important features of visual information, feature lines exist in real objects and target scenes. The characterization features of the pixels on the feature line are constructed. The pixels are classified and output by representing the eigenvalues to complete the classification of different target feature lines. The local gradient information of the points in the straight line segment is extracted and the midpoint descriptor is formed to match the straight line segment accurately. The edge detection is performed sequentially, the edge line of the object feature is extracted, and the edge principal point is obtained simultaneously according to the distance judgment. The research shows that the feature line matching method greatly reduces the calculation amount of matching and greatly improves the matching accuracy. The flexibility of building samples is strong, and different levels of sample forms can be selected according to different application requirements, and the robustness of matching and identification is good. The method is suitable for rapid detection and identification of object features, as well as product feature detection and recognition.

Research on Fast Detection and Recognition of Object Features Based on Feature Line Matching