REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION

The optical flow constraint equation of Horn-Schunck (OFCE-HS) is an algorithm used to compute motion estimation from the apparent motion of image sequences. To achieve real-time performance and high accuracy estimation for real-time system especially for machine vision application, numerous effo...

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Main Author: RUZALI, RUZALI
Format: Thesis
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.23030 /
Published: 2012
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access: http://utpedia.utp.edu.my/23030/1/Ruzali%27s%20Thesis%20v.4%2020120719%20after%20viva-voce%20%28final%29.pdf
http://utpedia.utp.edu.my/23030/
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spelling utp-utpedia.230302022-03-11T04:17:30Z http://utpedia.utp.edu.my/23030/ REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION RUZALI, RUZALI TK Electrical engineering. Electronics Nuclear engineering The optical flow constraint equation of Horn-Schunck (OFCE-HS) is an algorithm used to compute motion estimation from the apparent motion of image sequences. To achieve real-time performance and high accuracy estimation for real-time system especially for machine vision application, numerous efforts have been put to implement the OFCE-HS algorithm into hardware. However, so far there has not been a single solution reported to have achieved both real-time performance and high estimation accuracy. Therefore, the work reported in this thesis was set out with an objective to come up with a hardware solution to address the real-time and accuracy problem aforementioned. The objective was achieved by implementing high throughput hardware architecture that is able to support the high iteration (i.e. a minimum of fifty iterations) required by the OFCE-HS algorithm to achieve acceptable accuracy. In addition to the pipeline processing, two partitioning techniques were successfully implemented; first, on the frame of the image sequences and second, on the loop of the iterations. The optimized OFCE-HS hardware architecture was implemented on the FPGA Xilinx Spartan-3A DSP 1800A. 2012-07 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/23030/1/Ruzali%27s%20Thesis%20v.4%2020120719%20after%20viva-voce%20%28final%29.pdf RUZALI, RUZALI (2012) REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION. Masters thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
RUZALI, RUZALI
REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION
description The optical flow constraint equation of Horn-Schunck (OFCE-HS) is an algorithm used to compute motion estimation from the apparent motion of image sequences. To achieve real-time performance and high accuracy estimation for real-time system especially for machine vision application, numerous efforts have been put to implement the OFCE-HS algorithm into hardware. However, so far there has not been a single solution reported to have achieved both real-time performance and high estimation accuracy. Therefore, the work reported in this thesis was set out with an objective to come up with a hardware solution to address the real-time and accuracy problem aforementioned. The objective was achieved by implementing high throughput hardware architecture that is able to support the high iteration (i.e. a minimum of fifty iterations) required by the OFCE-HS algorithm to achieve acceptable accuracy. In addition to the pipeline processing, two partitioning techniques were successfully implemented; first, on the frame of the image sequences and second, on the loop of the iterations. The optimized OFCE-HS hardware architecture was implemented on the FPGA Xilinx Spartan-3A DSP 1800A.
format Thesis
author RUZALI, RUZALI
author_sort RUZALI, RUZALI
title REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION
title_short REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION
title_full REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION
title_fullStr REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION
title_full_unstemmed REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION
title_sort real-time horn-schunck optical flow hardware architecture for high accuracy motion estimation
publishDate 2012
url http://utpedia.utp.edu.my/23030/1/Ruzali%27s%20Thesis%20v.4%2020120719%20after%20viva-voce%20%28final%29.pdf
http://utpedia.utp.edu.my/23030/
_version_ 1741195897346195456
score 11.62408

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