The conventional matching methods are easily affected by scene occlusions

light and noise. On the other hand

the relationship of correspondence between model and image need to be built

which makes the matching process become more complicated. Then Hausdorff distance is used and the drawbacks of conventional partial Hausdorff distance is analyzed and corrected. To achieve image matching quickly

the concept of information measures is introduced into image matching to extract the edge characteristic points based on edge detection

and the similarity measures are constructed based on modified Hausdorff distance

then a new matching strategy is proposed based on information measures and Hausdorff distance. In this method

a process of pre-matching is used to pick out the unimportant regions by making use of some general information

such as the proportion of pixels' number in the range of preset gray level or preset information measure value

which speeds up the matching process greatly. The proposed strategy improves the resistance to noise and gives the criteria of parameter selection to some extent. In addition

this method matches the image occlusions correctly and overcomes the mismatching problems that induced by noise

spurious edge segments and outlier points. The experimental results demonstrate that the proposed strategy is feasible and effective.