2results about How to "Simplify the matching process" patented technology

The invention discloses a circular hole detection and binocular matching method considering peripheral features. Comprising the following steps: constructing a three-dimensional part model according to structure parameters of a to-be-detected part, and constructing a data set through a rendering method by utilizing the three-dimensional part model; constructing a circular hole detection and binocular matching model, and training by using the data set to obtain a trained circular hole detection and binocular matching model; the circular hole detection and binocular matching model comprises a feature extraction backbone network, a feature encoder, two parallel feature decoders and a feature segmentation module, and the two feature decoders are respectively a detection decoder and a matching decoder; and acquiring an actual binocular image of a to-be-detected part, and inputting the actual binocular image into the trained round hole detection and binocular matching model to obtain a round hole detection result. According to the method, the position relation between the circular holes and peripheral features such as the environment can be effectively utilized, and the accuracy and robustness of binocular matching and segmentation in a complex scene are improved.

The application discloses a method for reducing fingerprint identification and forgery by using ORB image local features, comprising the following steps: S1, extracting minutia points of a to-be-matched fingerprint image; S2, marking a region around the minutia points of the to-be-matched fingerprint image, and extracting ORB key points of the marked region; S3, calculating minutia point pairs of the to-be-matched fingerprint image, and judging whether the calculated minutia point pairs are within a preset minutia point pair range; if not, the to-be-matched fingerprint image fails to match; if yes, step S4 is performed; S4, matching the ORB key points of the to-be-matched fingerprint image according to the calculated minutia point pairs, and judging whether the number of the matched ORB key points is greater than or equal to a preset ORB key point matching number; if not, the to-be-matched fingerprint image fails to match; if yes, step S5 is performed; and S5, the to-be-matched fingerprint image succeeds in matching.