Virtual reality of recognition technologies of the improved contour coding image based on level set and neural network models

摘要

Abstract Image contour-based feature extraction method has been applied to some fields of image recognition and virtual reality. However, image contour features are easily susceptible to factors like noise, rotation and thresholds during extraction and processing. To solve the above problem, this paper proposes a contour coding image recognition algorithm based on level set and BP neural network models. Firstly, level set model is employed to extract the contours of images. Secondly, image coding method proposed herein is used to code images horizontally, vertically and obliquely. At last, BP neural network model is trained to recognize the image codes. Validity of the proposed algorithm is verified by using a set of actual engineering part images as well as MPEG and PLANE databases. The results show that the proposed method achieves high recognition rate and requires small samples, which also exhibits good robustness to external disturbances such as noise and image scaling and rotation.