An Improved Edge Structure Weighted Hausdorff Distance for Template Matching
| Autor: | De Cheng Yuan, Guo Gang Wang, Hong Yan Shi |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Matching (graph theory)
business.industry Template matching Cognitive neuroscience of visual object recognition Structure (category theory) Pattern recognition General Medicine Structure tensor Hausdorff distance Feature (computer vision) Enhanced Data Rates for GSM Evolution Artificial intelligence business Mathematics |
| Zdroj: | Advanced Engineering Forum. :163-168 |
| ISSN: | 2234-991X |
| DOI: | 10.4028/www.scientific.net/aef.6-7.163 |
| Popis: | Template matching based on a Hausdorff distance (HD) approach become popular for object recognition. In this paper, we present a newly improved edge structure weighted HD (ESW-HD) algorithm for object recognition. We use edge points as the feature of the model, and construct the structure tensor by edge intensity and edge gradient. Then, the HD is weighted by the structure tensors. This work illustrates the ESW-HD algorithm by template edge matching which uses edge points and its edge adjacent structure information to perform the image matching. The experimental results show that the improved HD matching method can achieve a good performance level in terms of matching accuracy, even in a noisy environment when compared with the conventional approaches for object recognition. |
| Databáze: | OpenAIRE |
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