An Image Matching Strategy Based on Information Measures and Hausdorff Distance[J]. Journal of Image and Graphics, 2004, 9(11): 1314. DOI: 10.11834/jig.2004011253.
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.