Research Article
Optimization of Degree Regenced Segment Lines Detection Using Ant Colony Optimization Algorithm
@INPROCEEDINGS{10.4108/eai.20-1-2018.2281931, author={Johnie Rogers Swanda Pasaribu and Elviawaty M. Zamzami and Pahala Sirait and A M H Pardede Sirait and M. Heikal}, title={Optimization of Degree Regenced Segment Lines Detection Using Ant Colony Optimization Algorithm}, proceedings={Proceedings of the 1st Workshop on Multidisciplinary and Its Applications Part 1, WMA-01 2018, 19-20 January 2018, Aceh, Indonesia}, publisher={EAI}, proceedings_a={WMA-1}, year={2019}, month={9}, keywords={edge detection ant colony optimization compass operator}, doi={10.4108/eai.20-1-2018.2281931} }
- Johnie Rogers Swanda Pasaribu
Elviawaty M. Zamzami
Pahala Sirait
A M H Pardede Sirait
M. Heikal
Year: 2019
Optimization of Degree Regenced Segment Lines Detection Using Ant Colony Optimization Algorithm
WMA-1
EAI
DOI: 10.4108/eai.20-1-2018.2281931
Abstract
Edge detection is an important operation in digital image analysis to get a better image as needed. In the edge detection process to determine the location of the points that are the edge of the object. The purpose of edge detection is to detect borders that constrain two areas of image, object and background. In this paper will be done pre-image processing by eliminating noise using Geometric Mean Filter algorithm then will be done edge detection using compass operators and will be calculated MSE and PSNR, then as a comparison with line detection with Hough Transform algorithm and edge detection with Ant Colony algorithm. The results obtained are reduced error and increase Peak to Noise Ratio (PSNR).
Copyright © 2018–2024 EAI