Evidence map›Paper›PMID 36904935›Full record

ArticleSensors (Basel, Switzerland)2023

An Anti-Noise Fast Circle Detection Method Using Five-Quadrant Segmentation.

Yun Ou, Honggui Deng, Yang Liu, Zeyu Zhang, Xin Lan

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Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yun OuSchool of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China.ORCID 0000-0002-5104-6645
Honggui DengSchool of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China.
Yang LiuSchool of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China.
Zeyu ZhangSchool of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China.ORCID 0000-0002-7583-1867
Xin LanSchool of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China.ORCID 0000-0001-9255-848X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracting circle information from images has always been a basic problem in computer vision. Common circle detection algorithms have some defects, such as poor noise resistance and slow computation speed. In this paper, we propose an anti-noise fast circle detection algorithm. In order to improve the anti-noise of the algorithm, we first perform curve thinning and connection on the image after edge extraction, then suppress noise interference by the irregularity of noise edges and extract circular arcs by directional filtering. In order to reduce the invalid fitting and speed up the running speed, we propose a circle fitting algorithm with five quadrants, and improve the efficiency of the algorithm by the idea of "divide and conquer". We compare the algorithm with RCD, CACD, WANG and AS on two open datasets. The results show that we have the best performance under noise while keeping the speed of the algorithm.

Indexed as

anti-noisecircle detectionfive-quadrant segmentation

Identifiers

PMID36904935
PMCPMC10007019

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.