Object Recognition Of Projective Invariance Based On Wavelet Computation

Object recognition is one of the important parts of computer vision, and has been widely applied in the fields such as military affairs and automatization. Description and recognition of plane has been processed depend on the geometry model of continental group and affine group anciently, with the development of the computer vision application, people attaches importance to the investigation of the perspective invariants, thus the investigation of perspective invariants gradually become an important problem in the computer vision.In this paper, we study the method of recognizing object in its 2-D image. The projective transform occurs in the 2-D image process, therefore in order to recognize object, we have to find projective-invariant shape descriptor of object. Firstly in the stage of image segmentation, on the basis of comparing three edge detector in common use, we propose a new method of edge detection, which is combing Robert detector and contour tracing, gained the edge curve of velvet and continuum. After getting curve in the stage of image segmentation, we propose the method of detecting projective-invariant key points on the interpolation, constructing relevant sutra frame, and processing analysis towards sutra frame using wavelet theory, gained the object recognition invariants. Finally we testify the validity of the invariant proposed in this paper. In this paper, since the invariant is selected based on the part of edge, the object curtained can be recognized.