A new fast efficient non-maximum suppression algorithm based on image segmentation
In this paper, the problem of finding local extrema in grayscale images is considered. The known non-maximum suppression algorithms provide high speed, but only single-pixel extrema are extracted, skipping regions formed by multi-pixel extrema. Morphological algorithms allow toextract all extrema bu...
Saved in:
| Main Authors: | , , |
|---|---|
| Other Authors: | , |
| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2020-08-01.
|
| Subjects: | |
| Online Access: | Get fulltext |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| LEADER | 02697 am a22003253u 4500 | ||
|---|---|---|---|
| 001 | ijeecs21069_14025 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Al-Furaiji, Oday Jasim |e author |
| 100 | 1 | 0 | |a Shatt Al-Arab University College, Department of Computer Science |e contributor |
| 100 | 1 | 0 | |a Belarusian State University of Informatics and Radioelectronics |q (BSUIR) |e contributor |
| 700 | 1 | 0 | |a Anh Tuan, Nguyen |e author |
| 700 | 1 | 0 | |a Tsviatkou, Viktar Yurevich |e author |
| 245 | 0 | 0 | |a A new fast efficient non-maximum suppression algorithm based on image segmentation |
| 260 | |b Institute of Advanced Engineering and Science, |c 2020-08-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21069 | ||
| 520 | |a In this paper, the problem of finding local extrema in grayscale images is considered. The known non-maximum suppression algorithms provide high speed, but only single-pixel extrema are extracted, skipping regions formed by multi-pixel extrema. Morphological algorithms allow toextract all extrema but its maxima and minima are processed separately with high computational complexity by iterative processing based on image reconstruction using image morphological dilation and erosion. In this paper a new fast efficient non-maximum suppression algorithm based on image segmentation and border analysis is proposed. The proposed algorithm considers homogeneous areas, which are formed by multi-pixel extrema and are the local maxima or minima in relation to adjacent areas, eliminating iterative processing of non-extreme pixels and assigning label numbers to local extrema during their search. The proposed algorithm allowed to increase the accuracy of local extremum extraction in comparison with known non-maximum suppression algorithms and reduce the computational complexity and the use of RAM in comparison with the morphological algorithms. | ||
| 540 | |a Copyright (c) 2020 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a Feature point; Image segmentation; Local extrema; Local maxima; Non-maximum suppression; Region growing | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 19, No 2: August 2020; 1062-1070 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v19.i2 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21069/14025 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21069/14025 |z Get fulltext |