Key Problems Research In Multi-value Template Matching

Since digital image processing has been a special subject, it was applied in several fields from the initial industry and commerce to the art, culture and people's daily life. The image mate are indispensable components in the pattern recognition system, and it was also one of the most difficult and commonly problem. This topic mainly aims is to research the multi-value template matching method and the key question, Main content include following several aspects.In template image segmentation. First, this text proposed the segmentation algorithm which based on gradation to segment template, this threshold segmentation algorithm which transform the process of finding optimal threshold to the process of finding maximal likeness degree with optimal threshold between source picture and after segmentation picture. Taking the template matches formula as the standards of the evaluating likeness degree, and designing a segmentation algorithm based on the histogram which equivalent the template matching. The theoretical and experiment results showed that the new method has good dissection effect, and the speed is quick. Then the text put forward the segmentation algorithm which based on edge to segment template, put forward the concept of edge deviation degree . Finally, this text propose the method to promote to the general picture segmentation.In fast image matching, this text put forward the fast-matching method which base on the multi-value template, made the template picture which have been segmented as new template to match image, then utilized the same district of D-template and use a iteration method to reduce the calculation. The experiment got the more satisfied result. Finally, put forward the match difference concept and carry on measuring to the difference between the result of multi-value template matching and Source template matching.In the optimal number of threshold, this text chose the standards of how to get the number of image optimal threshold, Selected the best number of threshold to segment source template, Guarantees the low complex in fast matching. Then it has research the different segmentation method to the number of optimal threshold and the relationship betweentemplate characteristic and choice of optimal threshold .