An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation

Joint Authors

Dong, Enzeng
Zhao, Yao
Yu, Xiao
Zhu, Junchao
Chen, Chao

Source

Journal of Sensors

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2015-12-22

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Civil Engineering

Abstract EN

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.

American Psychological Association (APA)

Dong, Enzeng& Zhao, Yao& Yu, Xiao& Zhu, Junchao& Chen, Chao. 2015. An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation. Journal of Sensors،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1110322

Modern Language Association (MLA)

Dong, Enzeng…[et al.]. An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation. Journal of Sensors No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1110322

American Medical Association (AMA)

Dong, Enzeng& Zhao, Yao& Yu, Xiao& Zhu, Junchao& Chen, Chao. An Improved NMS-Based Adaptive Edge Detection Method and Its FPGA Implementation. Journal of Sensors. 2015. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1110322

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1110322