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Kernel Sets in Compass Edge Detection

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Authors
Čisar, Petar
Maravić-Cisar, Sanja
Markoski, Branko
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Abstract
Edge detection is an important operation in the analysis of a digital image and includes a set of mathematical methods to identify points of discontinuity. For this purpose, different algorithms are used for estimating image gradient. Many edge detection techniques are implemented with convolution mask and based on discrete approximations to differential operators. Differential operations measure the rate of change in the image brightness function. The compass approach implies taking a single mask and rotating it to major compass orientations. Using a suitable programming environment, this paper provides a comparative visual analysis of several digital images, with the ability to change the kernel set in compass edge detection.
Source:
14th IEEE international symposium on computational intelligence and informatics (cinti), 2013, 239-242
Publisher:
  • IEEE, New York

DOI: 10.1109/CINTI.2013.6705199

ISSN: 2380-8586

WoS: 000345626300040

Scopus: 2-s2.0-84893723978
[ Google Scholar ]
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URI
http://jakov.kpu.edu.rs/handle/123456789/514
Collections
  • Radovi istraživača / Researchers' publications
Institution/Community
Jakov
TY  - CONF
AU  - Čisar, Petar
AU  - Maravić-Cisar, Sanja
AU  - Markoski, Branko
PY  - 2013
UR  - http://jakov.kpu.edu.rs/handle/123456789/514
AB  - Edge detection is an important operation in the analysis of a digital image and includes a set of mathematical methods to identify points of discontinuity. For this purpose, different algorithms are used for estimating image gradient. Many edge detection techniques are implemented with convolution mask and based on discrete approximations to differential operators. Differential operations measure the rate of change in the image brightness function. The compass approach implies taking a single mask and rotating it to major compass orientations. Using a suitable programming environment, this paper provides a comparative visual analysis of several digital images, with the ability to change the kernel set in compass edge detection.
PB  - IEEE, New York
C3  - 14th IEEE international symposium on computational intelligence and informatics (cinti)
T1  - Kernel Sets in Compass Edge Detection
SP  - 239
EP  - 242
DO  - 10.1109/CINTI.2013.6705199
UR  - conv_1122
ER  - 
@conference{
author = "Čisar, Petar and Maravić-Cisar, Sanja and Markoski, Branko",
year = "2013",
abstract = "Edge detection is an important operation in the analysis of a digital image and includes a set of mathematical methods to identify points of discontinuity. For this purpose, different algorithms are used for estimating image gradient. Many edge detection techniques are implemented with convolution mask and based on discrete approximations to differential operators. Differential operations measure the rate of change in the image brightness function. The compass approach implies taking a single mask and rotating it to major compass orientations. Using a suitable programming environment, this paper provides a comparative visual analysis of several digital images, with the ability to change the kernel set in compass edge detection.",
publisher = "IEEE, New York",
journal = "14th IEEE international symposium on computational intelligence and informatics (cinti)",
title = "Kernel Sets in Compass Edge Detection",
pages = "239-242",
doi = "10.1109/CINTI.2013.6705199",
url = "conv_1122"
}
Čisar, P., Maravić-Cisar, S.,& Markoski, B.. (2013). Kernel Sets in Compass Edge Detection. in 14th IEEE international symposium on computational intelligence and informatics (cinti)
IEEE, New York., 239-242.
https://doi.org/10.1109/CINTI.2013.6705199
conv_1122
Čisar P, Maravić-Cisar S, Markoski B. Kernel Sets in Compass Edge Detection. in 14th IEEE international symposium on computational intelligence and informatics (cinti). 2013;:239-242.
doi:10.1109/CINTI.2013.6705199
conv_1122 .
Čisar, Petar, Maravić-Cisar, Sanja, Markoski, Branko, "Kernel Sets in Compass Edge Detection" in 14th IEEE international symposium on computational intelligence and informatics (cinti) (2013):239-242,
https://doi.org/10.1109/CINTI.2013.6705199 .,
conv_1122 .

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