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 inTransactions on electrical and electronic materials pp. 150 - 156
Main Authors 이주성, 안호명, 김주연
Format Journal Article
LanguageEnglish
Published 한국전기전자재료학회 01.04.2020
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ISSN1229-7607
2092-7592
DOI10.1007/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
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
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  fullname: 김주연
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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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