Efficient Sampling Strategy and Refinement Strategy forRandomized Circle Detection
碩士 === 國立臺灣科技大學 === 資訊工程系 === 98 === Circle-detection is an important and fundamental operation in image processing and pattern recognition. This thesis first presents a new gradient line-based sampling strategy to determine a candidate circle and the determined candidate circle has higher probabili...
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/56576919340315401116 |
| Summary: | 碩士 === 國立臺灣科技大學 === 資訊工程系 === 98 === Circle-detection is an important and fundamental operation in image
processing and pattern recognition. This thesis first presents a new
gradient line-based sampling strategy to determine a candidate
circle and the determined candidate circle has higher probability to
be promoted to a true circle when compared with the traditional
randomized strategy; it leads to significantly computational effect.
Further, for enhancing the detection accuracy, a new revoting-based
refinement strategy is presented. Experimental results demonstrated
that our proposed gradient line-based sampling strategy and
revoting-based refinement strategy can significantly improve
computing time performance and the detection accuracy for circle
detection when compared with previous randomized related algorithms.
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