An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation
For improving the processing speed and accuracy of edge detection, an adaptive edge detection method based on improved NMS (nonmaximum suppression) was proposed in this paper. In the method, the gradient image was computed by four directional Sobel operators. Then, the gradient image was processed b...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2016-01-01
|
Series: | Journal of Sensors |
Online Access: | http://dx.doi.org/10.1155/2016/1470312 |
id |
doaj-188f0e60c3ca4db4a55e58403d72118c |
---|---|
record_format |
Article |
spelling |
doaj-188f0e60c3ca4db4a55e58403d72118c2020-11-24T23:27:10ZengHindawi LimitedJournal of Sensors1687-725X1687-72682016-01-01201610.1155/2016/14703121470312An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA ImplementationEnzeng Dong0Yao Zhao1Xiao Yu2Junchao Zhu3Chao Chen4Key Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin 300384, ChinaKey Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin 300384, ChinaKey Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin 300384, ChinaKey Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin 300384, ChinaKey Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin 300384, ChinaFor improving the processing speed and accuracy of edge detection, an adaptive edge detection method based on improved NMS (nonmaximum suppression) was proposed in this paper. In the method, the gradient image was computed by four directional Sobel operators. Then, the gradient image was processed by using NMS method. By defining a power map function, the elements values of gradient image histogram were mapped into a wider value range. By calculating the maximal between-class variance according to the mapped histogram, the corresponding threshold was obtained as adaptive threshold value in edge detection. Finally, to be convenient for engineering application, the proposed method was realized in FPGA (Field Programmable Gate Array). The experiment results demonstrated that the proposed method was effective in edge detection and suitable for real-time application.http://dx.doi.org/10.1155/2016/1470312 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Enzeng Dong Yao Zhao Xiao Yu Junchao Zhu Chao Chen |
spellingShingle |
Enzeng Dong Yao Zhao Xiao Yu Junchao Zhu Chao Chen An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation Journal of Sensors |
author_facet |
Enzeng Dong Yao Zhao Xiao Yu Junchao Zhu Chao Chen |
author_sort |
Enzeng Dong |
title |
An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation |
title_short |
An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation |
title_full |
An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation |
title_fullStr |
An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation |
title_full_unstemmed |
An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation |
title_sort |
improved nms-based adaptive edge detection method and its fpga implementation |
publisher |
Hindawi Limited |
series |
Journal of Sensors |
issn |
1687-725X 1687-7268 |
publishDate |
2016-01-01 |
description |
For improving the processing speed and accuracy of edge detection, an adaptive edge detection method based on improved NMS (nonmaximum suppression) was proposed in this paper. In the method, the gradient image was computed by four directional Sobel operators. Then, the gradient image was processed by using NMS method. By defining a power map function, the elements values of gradient image histogram were mapped into a wider value range. By calculating the maximal between-class variance according to the mapped histogram, the corresponding threshold was obtained as adaptive threshold value in edge detection. Finally, to be convenient for engineering application, the proposed method was realized in FPGA (Field Programmable Gate Array). The experiment results demonstrated that the proposed method was effective in edge detection and suitable for real-time application. |
url |
http://dx.doi.org/10.1155/2016/1470312 |
work_keys_str_mv |
AT enzengdong animprovednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT yaozhao animprovednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT xiaoyu animprovednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT junchaozhu animprovednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT chaochen animprovednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT enzengdong improvednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT yaozhao improvednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT xiaoyu improvednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT junchaozhu improvednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation AT chaochen improvednmsbasedadaptiveedgedetectionmethodanditsfpgaimplementation |
_version_ |
1725553043445907456 |