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In order to restrain the high sensitivity to image noise and non-linearity transform as for the traditional automatic matching algorithm in the system of image-based modeling, a new simplified algorithm based on SIFT (scale invariant feature transform) was provided. Firstly, for avoiding the problem of losing of information, position excursion and the fake keypoints, the features were detected and captured in multi-scale space. Secondly, the reversible image matching algorithm was adopted based on simplifying SIFT local feature descriptor for accurate matching. Lastly, the matching algorithm was optimized by using RANSAC and the approximate nearest neighbor algorithm in the light of epipolar constraints. The experimental results demonstrated the robustness and efficiency of the algorithm.