基于角仿射不变的特征匹配

同一场景的不同图像匹配是计算机视觉中的一个基本问题，在诸如三维重建、对象识别和分类、图像配准和相机自校正等应用中，特征匹配都是一个关键步骤。为解决三维场景重建问题，通过改进目前特征匹配的不足，提出了一种基于角仿射不变的特征匹配算法。该方法是使用角作为图像匹配选取的特征，通过仿射不变处理来消除图像缩放、扭曲、旋转和平移产生的影响，实验表明，该算法具有良好的匹配性能，可以对差异较大的图像对进行特征匹配。

Feature Matching Based on Corner Affine Invariant

Different image matching of the same scene is a key problem in computer vision, and is frequently used in three-dimensional object reconstruction,object recognition,image alignment,camera self-calibration and so on. Feature point matching is the most common one among a11 kinds of image matching.To solve the problem of 3-dimensional scene reconstruction, and to improve the performance of present feature point matching, a matching scheme which is invariant to perspective deformation induced by changes in viewpoint is required. This paper proposes a novel algorithm of Feature Match Based on Corner Affine Invariant. It selects corners as extracting feature of the image matching, and these corners are characterized by their orientation and angular width. Through calculating affine invariant, the influence of image stretch, skew, rotation, translation and 1ighting conditions is removed, and by using the epipolar geometry as a matching constraint, those outliers are eliminated too. Consequently we realize the feature matching of image pairs with much difference. And the experimentation shows that the algorithm has high matching accuracy and good matching performance.