Edge detection of aerial images using artificial bee colony algorithm

Elif Deniz Yelmenoglu; Nurdan Akhan Baykan

doi:10.51354/mjen.1053446

EN

Edge detection of aerial images using artificial bee colony algorithm

Abstract

Edge detection techniques are the one of the best popular and significant implementation areas of the image processing. Moreover, image processing is very widely used in so many fields. Therefore, lots of methods are used in the development and the developed studies provide a variety of solutions to problems of computer vision systems. In many studies, metaheuristic algorithms have been used for obtaining better results. In this paper, aerial images are used for edge information extraction by using Artificial Bee Colony (ABC) Optimization Algorithm. Procedures were performed on gray scale aerial images which are taken from RADIUS/DARPA-IU Fort Hood database. Initially bee colony size was specified according to sizes of images. Then a threshold value was set for each image, which related with images’ standard deviation of gray scale values. After the bees were distributed, fitness values and probability values were computed according to gray scale value. While appropriate pixels were specified, the other ones were being abandoned and labeled as banned pixels therefore bees never located on these pixels again. So the edges were found without the need to examine all pixels in the image. Our improved method’s results are compared with other results found in the literature according to detection error and similarity calculations’. All the experimental results show that ABC can be used for obtaining edge information from images.

Keywords

Image processing, Edge detection, Artificial Bee Colony Optimization, Aerial Images

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Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Authors

Elif Deniz Yelmenoglu ^*
0000-0002-3645-3445
Türkiye

Nurdan Akhan Baykan
0000-0002-4289-8889
Türkiye

Publication Date

June 30, 2022

Submission Date

January 4, 2022

Acceptance Date

May 12, 2022

Published in Issue

Year 2022 Volume: 10 Number: 1

DOI

https://doi.org/10.51354/mjen.1053446

IZ

https://izlik.org/JA98LG67EL

APA

Yelmenoglu, E. D., & Akhan Baykan, N. (2022). Edge detection of aerial images using artificial bee colony algorithm. MANAS Journal of Engineering, 10(1), 73-80. https://doi.org/10.51354/mjen.1053446

AMA

1.Yelmenoglu ED, Akhan Baykan N. Edge detection of aerial images using artificial bee colony algorithm. MJEN. 2022;10(1):73-80. doi:10.51354/mjen.1053446

Chicago

Yelmenoglu, Elif Deniz, and Nurdan Akhan Baykan. 2022. “Edge Detection of Aerial Images Using Artificial Bee Colony Algorithm”. MANAS Journal of Engineering 10 (1): 73-80. https://doi.org/10.51354/mjen.1053446.

EndNote

Yelmenoglu ED, Akhan Baykan N (June 1, 2022) Edge detection of aerial images using artificial bee colony algorithm. MANAS Journal of Engineering 10 1 73–80.

IEEE

[1]E. D. Yelmenoglu and N. Akhan Baykan, “Edge detection of aerial images using artificial bee colony algorithm”, MJEN, vol. 10, no. 1, pp. 73–80, June 2022, doi: 10.51354/mjen.1053446.

ISNAD

Yelmenoglu, Elif Deniz - Akhan Baykan, Nurdan. “Edge Detection of Aerial Images Using Artificial Bee Colony Algorithm”. MANAS Journal of Engineering 10/1 (June 1, 2022): 73-80. https://doi.org/10.51354/mjen.1053446.

JAMA

1.Yelmenoglu ED, Akhan Baykan N. Edge detection of aerial images using artificial bee colony algorithm. MJEN. 2022;10:73–80.

MLA

Yelmenoglu, Elif Deniz, and Nurdan Akhan Baykan. “Edge Detection of Aerial Images Using Artificial Bee Colony Algorithm”. MANAS Journal of Engineering, vol. 10, no. 1, June 2022, pp. 73-80, doi:10.51354/mjen.1053446.

Vancouver

1.Elif Deniz Yelmenoglu, Nurdan Akhan Baykan. Edge detection of aerial images using artificial bee colony algorithm. MJEN. 2022 Jun. 1;10(1):73-80. doi:10.51354/mjen.1053446

Manas Journal of Engineering

16155

Abstract

Edge detection of aerial images using artificial bee colony algorithm

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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