Implementation of the High-Speed Feature Extraction Algorithm Based on Energy Effi cient Threshold Value Selection
This paper proposes an implementation method of high-speed feature extraction algorithm. The proposed approach is based on the block type classifi cation algorithm, which can reduce the computational complexity required for feature detection by re-using the threshold value when the same block type o...
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Published in | Transactions on electrical and electronic materials pp. 150 - 156 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
한국전기전자재료학회
01.04.2020
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Subjects | |
Online Access | Get full text |
ISSN | 1229-7607 2092-7592 |
DOI | 10.1007/s42341-020-00188-x |
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Abstract | This paper proposes an implementation method of high-speed feature extraction algorithm. The proposed approach is based on the block type classifi cation algorithm, which can reduce the computational complexity required for feature detection by re-using the threshold value when the same block type occurred in same index of successive image. The experiment was carried out for quantitative analysis as the image resolution and block size were changed. The experiment results have shown that the better data consistency with the larger the block size and the smaller the image resolution, the matching probability of the threshold value was 97.99% on average when the block size was 128 × 128. Applying the proposed method to the Canny edge detection can completely eliminate the latency required for image processing of adaptive threshold value calculation, which requires significant computing complexity if the block type overlaps with the previous frame. By applying block type sorting algorithm to various feature detection algorithms in this way, it is expected that time needed for computation can be reduced. KCI Citation Count: 1 |
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AbstractList | This paper proposes an implementation method of high-speed feature extraction algorithm. The proposed approach is based on the block type classifi cation algorithm, which can reduce the computational complexity required for feature detection by re-using the threshold value when the same block type occurred in same index of successive image. The experiment was carried out for quantitative analysis as the image resolution and block size were changed. The experiment results have shown that the better data consistency with the larger the block size and the smaller the image resolution, the matching probability of the threshold value was 97.99% on average when the block size was 128 × 128. Applying the proposed method to the Canny edge detection can completely eliminate the latency required for image processing of adaptive threshold value calculation, which requires significant computing complexity if the block type overlaps with the previous frame. By applying block type sorting algorithm to various feature detection algorithms in this way, it is expected that time needed for computation can be reduced. KCI Citation Count: 1 |
Author | 김주연 안호명 이주성 |
Author_xml | – sequence: 1 fullname: 이주성 organization: (재) 실감교류인체감응솔루션연구단) – sequence: 2 fullname: 안호명 organization: (오산대학교) – sequence: 3 fullname: 김주연 organization: (울산대학교) |
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Snippet | This paper proposes an implementation method of high-speed feature extraction algorithm. The proposed approach is based on the block type classifi cation... |
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Title | Implementation of the High-Speed Feature Extraction Algorithm Based on Energy Effi cient Threshold Value Selection |
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