Efficient Strategies for Computing Euler Number of a 3D Binary Image
As an important topological property for a 3D binary image, the Euler number can be computed by finding specific a voxel block with 2 × 2 × 2 voxels, named the voxel pattern, in the image. In this paper, we introduce three strategies for enhancing the efficiency of a voxel-pattern-based Euler number...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/7/1726 |
| _version_ | 1797608093567156224 |
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| author | Bin Yao Haochen He Shiying Kang Yuyan Chao Lifeng He |
| author_facet | Bin Yao Haochen He Shiying Kang Yuyan Chao Lifeng He |
| author_sort | Bin Yao |
| collection | DOAJ |
| description | As an important topological property for a 3D binary image, the Euler number can be computed by finding specific a voxel block with 2 × 2 × 2 voxels, named the voxel pattern, in the image. In this paper, we introduce three strategies for enhancing the efficiency of a voxel-pattern-based Euler number computing algorithm used for 3D binary images. The first strategy is taking advantage of the voxel information acquired during computation to avoid accessing voxels repeatedly. This can reduce the average number of accessed voxels from 8 to 4 for processing a voxel pattern. Therefore, the efficiency of computation will be improved. The second strategy is scanning every two rows and processing two voxel patterns simultaneously in each scan. In this strategy, only three voxels need to be accessed when a voxel pattern is processed. The last strategy is determining the voxel accessing order in the processing voxel pattern and unifying the processing of the voxel patterns that have identical Euler number increments to one group in the computation. Although this strategy can theoretically reduce the average number of voxels accessed from 8 to 4.25 for processing a voxel pattern, it is more efficient than the above two strategies for moderate- and high-density 3D binary images. Experimental results demonstrated that the three algorithms with each of our proposed three strategies exhibit greater efficiency compared to the conventional Euler number computing algorithm based on finding specific voxel patterns in the image. |
| first_indexed | 2024-03-11T05:38:48Z |
| format | Article |
| id | doaj.art-65547bd44536480d81470ee3bd28fc5b |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T05:38:48Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-65547bd44536480d81470ee3bd28fc5b2023-11-17T16:34:46ZengMDPI AGElectronics2079-92922023-04-01127172610.3390/electronics12071726Efficient Strategies for Computing Euler Number of a 3D Binary ImageBin Yao0Haochen He1Shiying Kang2Yuyan Chao3Lifeng He4Artificial Intelligence Institute, School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an 710021, ChinaArtificial Intelligence Institute, School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an 710021, ChinaSchool of Computer Science, Xianyang Normal University, Xianyang 712000, ChinaFaculty of Advanced Business, Nagoya Sangyo University, Aichi 4888711, JapanArtificial Intelligence Institute, School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an 710021, ChinaAs an important topological property for a 3D binary image, the Euler number can be computed by finding specific a voxel block with 2 × 2 × 2 voxels, named the voxel pattern, in the image. In this paper, we introduce three strategies for enhancing the efficiency of a voxel-pattern-based Euler number computing algorithm used for 3D binary images. The first strategy is taking advantage of the voxel information acquired during computation to avoid accessing voxels repeatedly. This can reduce the average number of accessed voxels from 8 to 4 for processing a voxel pattern. Therefore, the efficiency of computation will be improved. The second strategy is scanning every two rows and processing two voxel patterns simultaneously in each scan. In this strategy, only three voxels need to be accessed when a voxel pattern is processed. The last strategy is determining the voxel accessing order in the processing voxel pattern and unifying the processing of the voxel patterns that have identical Euler number increments to one group in the computation. Although this strategy can theoretically reduce the average number of voxels accessed from 8 to 4.25 for processing a voxel pattern, it is more efficient than the above two strategies for moderate- and high-density 3D binary images. Experimental results demonstrated that the three algorithms with each of our proposed three strategies exhibit greater efficiency compared to the conventional Euler number computing algorithm based on finding specific voxel patterns in the image.https://www.mdpi.com/2079-9292/12/7/17263D imagetopological propertyEuler numberpattern recognitioncomputer vision |
| spellingShingle | Bin Yao Haochen He Shiying Kang Yuyan Chao Lifeng He Efficient Strategies for Computing Euler Number of a 3D Binary Image Electronics 3D image topological property Euler number pattern recognition computer vision |
| title | Efficient Strategies for Computing Euler Number of a 3D Binary Image |
| title_full | Efficient Strategies for Computing Euler Number of a 3D Binary Image |
| title_fullStr | Efficient Strategies for Computing Euler Number of a 3D Binary Image |
| title_full_unstemmed | Efficient Strategies for Computing Euler Number of a 3D Binary Image |
| title_short | Efficient Strategies for Computing Euler Number of a 3D Binary Image |
| title_sort | efficient strategies for computing euler number of a 3d binary image |
| topic | 3D image topological property Euler number pattern recognition computer vision |
| url | https://www.mdpi.com/2079-9292/12/7/1726 |
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