3-D Reconstruction Using Feature Points Extracted With Wavelet Transformation

The technique of image-based 3D reconstruction by means of images of the same scene with different viewpoints is studied in this massage.The usual 3-D reconstruction theory is proposed at fist. And the principle of Epipolar Geometry is introduced. Then several arithmetic how to solve fundamental matrix are discussed and the differences between them are presented.Vision stereo matching is one of the fundamental and significant problems in the study of the computer vision and contactless measurements. This technique makes it possible to reproduce a three-dimensional stereo by getting fundamental matrix through matching pixels. But it is the most difficult problem to be solved completely. In this work, the theory and algorithms for the stereo matching are studied in detail. The characteristic of corner points and feature points extracted by wavelet transformation are presented and compared. In this passage a nicer feature points matching method is proposed. At first, initial feature points pairs are being found with disparity area method and area supporting. In this way more correct feature point pairs are founded out and initial feature point pairs aggregation is built up. Then the aggregation is optimized continually through fundamental matrix method. On one hand, error point pairs are moved out. On the other hand, accurate fundamental matrix is built.At last, Experiments on the real images show that the algorithm in this work is applicable and effective.