A method of registration based on skeleton for 2-D shapes
The iterative closest point (ICP) algorithm is an accurate approach for the registration between two point sets on the same scale. However, number and noise of two point sets restrict good performance of ICP algorithm. This paper proposes a novel ICP algorithm based on skeleton (SKICP). The proposed...
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Published in | 2012 5th International Congress on Image and Signal Processing pp. 810 - 813 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.10.2012
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Abstract | The iterative closest point (ICP) algorithm is an accurate approach for the registration between two point sets on the same scale. However, number and noise of two point sets restrict good performance of ICP algorithm. This paper proposes a novel ICP algorithm based on skeleton (SKICP). The proposed algorithm is to denoise and speed up the point set matching process using skeleton of multi-scale point sets. Firstly, we extract the sparse skeletons from the lower resolution original point set, which have fewer points including its structure features. Secondly, the point set of skeletons is quickly matched in lower resolution, and an initial transformation matrix between two point sets acquired. Finally, the initial transformation matrix is used as the initial value for a more precise registration at high resolution using less iterations. Experiments demonstrate the SKICP algorithm has faster speed and better robustness on 2-D Shapes point set than the traditional ICP algorithm. |
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AbstractList | The iterative closest point (ICP) algorithm is an accurate approach for the registration between two point sets on the same scale. However, number and noise of two point sets restrict good performance of ICP algorithm. This paper proposes a novel ICP algorithm based on skeleton (SKICP). The proposed algorithm is to denoise and speed up the point set matching process using skeleton of multi-scale point sets. Firstly, we extract the sparse skeletons from the lower resolution original point set, which have fewer points including its structure features. Secondly, the point set of skeletons is quickly matched in lower resolution, and an initial transformation matrix between two point sets acquired. Finally, the initial transformation matrix is used as the initial value for a more precise registration at high resolution using less iterations. Experiments demonstrate the SKICP algorithm has faster speed and better robustness on 2-D Shapes point set than the traditional ICP algorithm. |
Author | Ce Li Xinying Luo Limei Xiao Shaoyi Du |
Author_xml | – sequence: 1 surname: Ce Li fullname: Ce Li organization: Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China – sequence: 2 surname: Xinying Luo fullname: Xinying Luo organization: Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China – sequence: 3 surname: Shaoyi Du fullname: Shaoyi Du organization: Inst. of Artificial Intell. & Robot., Xi'an Jiaotong Univ., Xi'an, China – sequence: 4 surname: Limei Xiao fullname: Limei Xiao organization: Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China |
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Snippet | The iterative closest point (ICP) algorithm is an accurate approach for the registration between two point sets on the same scale. However, number and noise of... |
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SubjectTerms | Computers Iterative Closest Point (ICP) Iterative closest point algorithm point set registration Robustness shape point sets skeleton |
Title | A method of registration based on skeleton for 2-D shapes |
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