Anomaly Detection on Railway Track Using Haralick Feature for Color Mapping Co-Occurrence Matrix-Reference-Cited by-同舟云学术

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Anomaly Detection on Railway Track Using Haralick Feature for Color Mapping Co-Occurrence Matrix

Published:2024-02-24 Issue: Volume: Page:301-306
ISSN:
Container-title:2024 4th Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS)
language:
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Author:

Liyuan Yang¹,Ming Yang²,Osman Ghazali³,Juan Xie⁴,Shishuai Yang⁵

Affiliation:

1. Kunming University,Kunming,China

2. Delong Software Technology (Tianjin) Co., Ltd,Tianjin,China

3. College of Computing, Informatics and Mathematics, Universiti Teknologi MARA,Machang,Malaysia

4. Kunming Metro Operation Co., Ltd.,Kunming,China

5. Chengdu Huanyu Zhiliao Technology Co., Ltd.,Chengdu,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10612845/10612846/10612948.pdf?arnumber=10612948

Reference14 articles.

1. Understanding the human factors contribution to railway accidents and incidents in Australia

2. Surface defect detection for high-speed rails using an inverse P-M diffusion model

3. Detection of rail faults using morphological feature extraction based image processing

4. Motion deviation rectifying method of dynamically measuring rail wear based on multi-line structured-light vision

5. A cyber-enabled visual inspection system for rail corrugation

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