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.