Face detection hardware accelerator using C-based high-level synthesis

Research has shown that Field Programmable Gate Array (FPGA) based implementation of image processing system results in high computational speed and energy efficiency. However, FPGA design has relatively long development time compared to alternative implementation platforms, such as those based on C...

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Main Author: Yeap, Han Chien
Format: Thesis
Language:English
Published: 2018
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Online Access:http://eprints.utm.my/id/eprint/79563/1/Yeap%2C%20Han%20Chien.pdf
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spelling my-utm-ep.795632018-10-31T12:58:38Z Face detection hardware accelerator using C-based high-level synthesis 2018 Yeap, Han Chien TK Electrical engineering. Electronics Nuclear engineering Research has shown that Field Programmable Gate Array (FPGA) based implementation of image processing system results in high computational speed and energy efficiency. However, FPGA design has relatively long development time compared to alternative implementation platforms, such as those based on Central Processing Unit, Graphical Processing Unit or Digital Signal Processor. Designing digital hardware at a higher level of abstraction is an effective way to shorten the development time. High-level synthesis (HLS) raises the abstraction level for designing digital circuit and translates a C-based description of the desired design into Hardware Descriptive Language. However, C-based HLS techniques are still lacking some maturity. In particular, existing works on applying C-based HLS to design hardware that accelerates window-based image processing algorithms are generally done in a trial and error manner, and usually results in non-optimal designs. Hence, there is a need for an effective procedure in applying C-based HLS that can lead to an optimized accelerator design. Therefore, the key contribution of this research is to present a systematic C-based HLS technique to be used in the design of hardware that accelerates image processing algorithm. The proposed C-based HLS design procedure is illustrated with a case study of the Sobel filter. The effectiveness of the proposed design technique is demonstrated by the case study of a Viola- Jones face detection accelerator targeted for implementation in FPGA. The proposed face detection hardware applies a pipelined architecture with task-level parallelism that allows concurrent execution on every sub-module. Experimental results show that the resulting accelerator module achieves a speed performance improvement of up to 12 times when compared to that of existing works. Tested on CMU+MIT database, the proposed accelerator achieves high detection accuracy of 88% and 46 false positives. Experimental results also show that the proposed design achieves up to 61 frames per second detection speed. This work demonstrates that the proposed Cbased HLS design methodology is effective for image processing hardware accelerator development. 2018 Thesis http://eprints.utm.my/id/eprint/79563/ http://eprints.utm.my/id/eprint/79563/1/Yeap%2C%20Han%20Chien.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic TK Electrical engineering
Electronics Nuclear engineering
spellingShingle TK Electrical engineering
Electronics Nuclear engineering
Yeap, Han Chien
Face detection hardware accelerator using C-based high-level synthesis
description Research has shown that Field Programmable Gate Array (FPGA) based implementation of image processing system results in high computational speed and energy efficiency. However, FPGA design has relatively long development time compared to alternative implementation platforms, such as those based on Central Processing Unit, Graphical Processing Unit or Digital Signal Processor. Designing digital hardware at a higher level of abstraction is an effective way to shorten the development time. High-level synthesis (HLS) raises the abstraction level for designing digital circuit and translates a C-based description of the desired design into Hardware Descriptive Language. However, C-based HLS techniques are still lacking some maturity. In particular, existing works on applying C-based HLS to design hardware that accelerates window-based image processing algorithms are generally done in a trial and error manner, and usually results in non-optimal designs. Hence, there is a need for an effective procedure in applying C-based HLS that can lead to an optimized accelerator design. Therefore, the key contribution of this research is to present a systematic C-based HLS technique to be used in the design of hardware that accelerates image processing algorithm. The proposed C-based HLS design procedure is illustrated with a case study of the Sobel filter. The effectiveness of the proposed design technique is demonstrated by the case study of a Viola- Jones face detection accelerator targeted for implementation in FPGA. The proposed face detection hardware applies a pipelined architecture with task-level parallelism that allows concurrent execution on every sub-module. Experimental results show that the resulting accelerator module achieves a speed performance improvement of up to 12 times when compared to that of existing works. Tested on CMU+MIT database, the proposed accelerator achieves high detection accuracy of 88% and 46 false positives. Experimental results also show that the proposed design achieves up to 61 frames per second detection speed. This work demonstrates that the proposed Cbased HLS design methodology is effective for image processing hardware accelerator development.
format Thesis
qualification_level Master's degree
author Yeap, Han Chien
author_facet Yeap, Han Chien
author_sort Yeap, Han Chien
title Face detection hardware accelerator using C-based high-level synthesis
title_short Face detection hardware accelerator using C-based high-level synthesis
title_full Face detection hardware accelerator using C-based high-level synthesis
title_fullStr Face detection hardware accelerator using C-based high-level synthesis
title_full_unstemmed Face detection hardware accelerator using C-based high-level synthesis
title_sort face detection hardware accelerator using c-based high-level synthesis
granting_institution Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department Faculty of Electrical Engineering
publishDate 2018
url http://eprints.utm.my/id/eprint/79563/1/Yeap%2C%20Han%20Chien.pdf
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