Research on Image Rotation Recognition Based on Histogram Feature Description

Abstract

Image recognition is a statistical pattern recognition problem in pattern recognition, which mainly includes four steps: image acquisition, preprocessing, feature extraction and selection, and pattern classification. In this paper, an omni-directional sequential feature description method based on F histogram is proposed. In this method, shapes are segmented by directional lines in all directions, the sequential feature description quantity between object segmentation segments in each direction line is calculated, the omni-directional sequential feature description quantity of shapes is constructed, and the similarity between shapes is calculated. In this method, the normal vector histogram is used as the point cloud feature descriptor, which can optimize the search of the corresponding point set, thus improving the ICP algorithm. By selecting the appropriate expansion center and expansion order, the recognition ability of the filter is improved. At the same time, using the concept of image moment, the characteristic moment vector of the target is constructed to identify the target with in-plane rotation and scale change. Based on the optimization strategy based on histogram feature description, the recognition speed of the algorithm is significantly improved.