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TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)
TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)
Current Result Document :
1
/ 9
´ÙÀ½°Ç
ÇѱÛÁ¦¸ñ(Korean Title)
Parallel Implementations of Digital Focus Indices Based on Minimax Search Using Multi-Core Processors
¿µ¹®Á¦¸ñ(English Title)
Parallel Implementations of Digital Focus Indices Based on Minimax Search Using Multi-Core Processors
ÀúÀÚ(Author)
Syed Anwar Hussainy F
Senthil Kumar Thillaigovindan
Ashok J
Sowmia K R
Jayashree K
Priya Vijay
HyungTae Kim
Duk-Yeon Lee
Dongwoon Choi
Jaehyeon Kang
Dong-Wook Lee
¿ø¹®¼ö·Ïó(Citation)
VOL 17 NO. 02 PP. 0542 ~ 0558 (2023. 02)
Çѱ۳»¿ë
(Korean Abstract)
¿µ¹®³»¿ë
(English Abstract)
A digital focus index (DFI) is a value used to determine image focus in scientific apparatus and smart devices. Automatic focus (AF) is an iterative and time-consuming procedure; however, its processing time can be reduced using a general processing unit (GPU) and a multi-core processor (MCP). In this study, parallel architectures of a minimax search algorithm (MSA) are applied to two DFIs: range algorithm (RA) and image contrast (CT). The DFIs are based on a histogram; however, the parallel computation of the histogram is conventionally inefficient because of the bank conflict in shared memory. The parallel architectures of RA and CT are constructed using parallel reduction for MSA, which is performed through parallel relative rating of the image pixel pairs and halved the rating in every step. The array size is then decreased to one, and the minimax is determined at the final reduction. Kernels for the architectures are constructed using open source software to make it relatively platform independent. The kernels are tested in a hexa-core PC and an embedded device using Lenna images of various sizes based on the resolutions of industrial cameras. The performance of the kernels for the DFIs was investigated in terms of processing speed and computational acceleration; the maximum acceleration was 32.6¡¿ in the best case and the MCP exhibited a higher performance.
Å°¿öµå(Keyword)
Heart Disease Prediction
accuracy
integrity
Machine learning
feature extraction
Neural networks
Effective Spectrum Sensing
Cognitive Radio Networks
Improved Support Vector Machine
Grasshopper Optimization-based Particle Swarm Algo
Digital Focus Index
Computer Vision Systems
Embedded Systems
Mobile Computing
Parallel Processing
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