Two-dimensional contour shape recognition and classification method based on local geometric feature sequence modeling

Abstract

The invention discloses a two-dimensional contour shape recognition and classification method based on local geometric feature sequence modeling, relates to the technical field of object recognition and classification, and solves the problem of the existing artificially adjusted and set shape features being too complex and the success rate of object two-dimensional contour shape recognition and classification For lower problems, the key points of the technical solution are: extract the local geometric features of the shape of the target object; convert the extracted feature information into time series information through LSTM; model the local geometric feature sequence based on the cyclic neural network; Connect the neural network for feature selection and balance, and obtain the classification result of the target object, which not only overcomes the shortcomings of artificially adjusting and setting shape features that are too complicated, but also significantly improves the success rate of object two-dimensional contour shape recognition and classification, and can distinguish different objects. 2D contour shapes and capture fine shape differences, including subtle local differences.

Description

technical field [0001] The invention relates to the technical field of object recognition and classification, more specifically, it relates to a two-dimensional contour shape recognition and classification method based on local geometric feature sequence modeling. Background technique [0002] The machine vision system converts the captured target into an image signal through the machine vision product (that is, the image capture device, which is divided into CMOS and CCD), and transmits it to a dedicated image processing system to obtain the shape information of the captured target. According to the pixel distribution and Information such as brightness and color is converted into digital signals; the image system performs various operations on these signals to extract the characteristics of the target, and then controls the on-site equipment actions according to the results of the discrimination. In many application fields of machine vision, the recognition and classificati...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a two-dimensional contour shape recognition and classification method based on local geometric feature sequence modeling, which has the feature of adding object shape features to the deep learning network, reflecting the relationship between object shape features, that is, overcoming artificial adjustment settings The shortcoming of the shape features being too complex has significantly improved the success rate of object two-dimensional contour shape recognition and classification, and can distinguish the two-dimensional contour shapes of different objects and capture fine shape differences, including subtle local differences

Images