With the aim to improve the stability and reliability of image matching,the Scale Invariant Feature Transform algorithm(SIFT) is applied to image feature extraction and image matching. The SIFT can find out those feature vectors in different scale spaces and can extract image features and image description with the invariantce for scale changes and rotations and the flexibility for illumination variation and affine transformation. In this paper,the SIFT method is used to get the special point of an image and its features. Then, the features are matched with the criterion of the nearest neighbor based on confidence. Finally,the features in the image with different illumination conditions,focus lengths and shooting angles are extrated and matched.The experimental results prove that the features extracted by SIFT method have excellent adaptive and accurate characteristics for the illumination,transfer and the rotation transform and have match accuracy more than 90%,which are useful for the fields of image recognition and image reconstruction.