Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs

Traffic sign recognition (TSR), taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF) detection and the k-nearest neighbor cl...

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Main Authors: Yan Han, Kushal Virupakshappa, Esdras Vitor Silva Pinto, Erdal Oruklu
Format: Article
Language:English
Published: MDPI AG 2015-12-01
Series:Electronics
Subjects:
Online Access:http://www.mdpi.com/2079-9292/4/4/1062
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spelling doaj-4669e41d2b49498dafdd823bff7c7d4f2020-11-24T23:10:32ZengMDPI AGElectronics2079-92922015-12-01441062108910.3390/electronics4041062electronics4041062Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAsYan Han0Kushal Virupakshappa1Esdras Vitor Silva Pinto2Erdal Oruklu3Department of Electrical and Computer Engineering, Illinois Institute of Technology, 3301 South Dearborn Street, Chicago, IL 60616, USADepartment of Electrical and Computer Engineering, Illinois Institute of Technology, 3301 South Dearborn Street, Chicago, IL 60616, USADepartment of Electrical and Computer Engineering, Illinois Institute of Technology, 3301 South Dearborn Street, Chicago, IL 60616, USADepartment of Electrical and Computer Engineering, Illinois Institute of Technology, 3301 South Dearborn Street, Chicago, IL 60616, USATraffic sign recognition (TSR), taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF) detection and the k-nearest neighbor classifier is introduced. The proposed system benefits from the SURF detection algorithm, which achieves invariance to rotated, skewed and occluded signs. In addition to the accuracy and robustness issues, a TSR system should target a real-time implementation on an embedded system. Therefore, a hardware/software co-design architecture for a Zynq-7000 FPGA is presented as a major objective of this work. The sign detection operations are accelerated by programmable hardware logic that searches the potential candidates for sign classification. Sign recognition and classification uses a feature extraction and matching algorithm, which is implemented as a software component that runs on the embedded ARM CPU.http://www.mdpi.com/2079-9292/4/4/1062traffic sign recognitionFPGASURF detectorhardware/software co-design
collection DOAJ
language English
format Article
sources DOAJ
author Yan Han
Kushal Virupakshappa
Esdras Vitor Silva Pinto
Erdal Oruklu
spellingShingle Yan Han
Kushal Virupakshappa
Esdras Vitor Silva Pinto
Erdal Oruklu
Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs
Electronics
traffic sign recognition
FPGA
SURF detector
hardware/software co-design
author_facet Yan Han
Kushal Virupakshappa
Esdras Vitor Silva Pinto
Erdal Oruklu
author_sort Yan Han
title Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs
title_short Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs
title_full Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs
title_fullStr Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs
title_full_unstemmed Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs
title_sort hardware/software co-design of a traffic sign recognition system using zynq fpgas
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2015-12-01
description Traffic sign recognition (TSR), taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF) detection and the k-nearest neighbor classifier is introduced. The proposed system benefits from the SURF detection algorithm, which achieves invariance to rotated, skewed and occluded signs. In addition to the accuracy and robustness issues, a TSR system should target a real-time implementation on an embedded system. Therefore, a hardware/software co-design architecture for a Zynq-7000 FPGA is presented as a major objective of this work. The sign detection operations are accelerated by programmable hardware logic that searches the potential candidates for sign classification. Sign recognition and classification uses a feature extraction and matching algorithm, which is implemented as a software component that runs on the embedded ARM CPU.
topic traffic sign recognition
FPGA
SURF detector
hardware/software co-design
url http://www.mdpi.com/2079-9292/4/4/1062
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AT esdrasvitorsilvapinto hardwaresoftwarecodesignofatrafficsignrecognitionsystemusingzynqfpgas
AT erdaloruklu hardwaresoftwarecodesignofatrafficsignrecognitionsystemusingzynqfpgas
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