Proceedings of the 2014 International Conference on Computer Science and Electronic Technology

image adaptive edge detection based on canny operator and multiwavelet denoising

Authors
Lin Zhang
Corresponding Author
Lin Zhang
Available Online January 2015.
DOI
10.2991/iccset-14.2015.74How to use a DOI?
Keywords
Edge Detection, Canny Operator, Multiwavelet Denoising, Adaptive Threshold
Abstract

Aim to problems of traditional canny operator, we propose an improved canny edge detection method. First, in order to overcome excessive smoothing, we use multiwave adaptive denoising method to instead of Gaussian filter. Then after obtaining non-maxima suppression image, we use mean values of gradient of entire image to adaptively select dual-threshold to instead of manually setting threshold. Our experiments are conducted on original image and noise image respectively. Experiments show compared with other traditional methods, this method can effectively remove noise, reduce the occurrence of pseudo-edge and obtain a more ideal edge detection effect finally.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2014 International Conference on Computer Science and Electronic Technology
Series
Advances in Computer Science Research
Publication Date
January 2015
ISBN
10.2991/iccset-14.2015.74
ISSN
2352-538X
DOI
10.2991/iccset-14.2015.74How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lin Zhang
PY  - 2015/01
DA  - 2015/01
TI  - image adaptive edge detection based on canny operator and multiwavelet denoising
BT  - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 335
EP  - 338
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccset-14.2015.74
DO  - 10.2991/iccset-14.2015.74
ID  - Zhang2015/01
ER  -