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Journals / Düzce Üniversitesi Bilim ve Teknoloji Dergisi / 2021 / Cilt: 9 - Sayı: 1

Detection of Rail Surface Defects by Full Spectrum Image Processing with the Help of Peridynamic Based Fuzzy Logic Algorithm

Peridinamik Tabanlı Bulanık Mantık Algoritması Yardımıyla Ray Yüzeyindeki Kusurların Tam Spektrum Görüntü İşleme ile Tespiti

Cihan MIZRAK
Pages
16–27
Publication Date
2022-10-12
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In addition, the algorithm developed with three different full spectrum sample ray defect images was tested and found to be better than the existing edge detection algorithms in the literature.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, a peridinamic based fuzzy logic algorithm has been developed for the detection of rail defects on a full spectrum image.
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Key Findings & Data:For the sample application, Gaussian masking of the full spectrum ray defect image in the gray scale definition set was performed and the derivation operations of the image from different directions and orders were obtained by using the peridynamic numerical derivation method.
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Conclusion & Impact:In addition, the algorithm developed with three different full spectrum sample ray defect images was tested and found to be better than the existing edge detection algorithms in the literature.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:peridinamik · bulanık mantık · dalga boyu

Abstract

In this study, a peridinamic based fuzzy logic algorithm has been developed for the detection of rail defects on a full spectrum image. For the sample application, Gaussian masking of the full spectrum ray defect image in the gray scale definition set was performed and the derivation operations of the image from different directions and orders were obtained by using the peridynamic numerical derivation method. Three different wavelength transformations were performed on the RGB and HSV scales of the image. By identifying the common points with the three most effective wavelengths applied on the fuzzy logic output, the rail defects are more pronounced. In addition, the algorithm developed with three different full spectrum sample ray defect images was tested and found to be better than the existing edge detection algorithms in the literature.

Özet

Bu çalışmada tam spektrum görüntü üzerinden ray kusurlarının belirlenmesine yönelik peridinamik tabanlı bulanık mantık algoritması geliştirilmiştir. Örnek uygulama için tam spektrum ray kusuru görüntüsünün, gri skala tanım kümesinde Gaussian maskelemesi gerçekleştirilmiş, görüntünün farklı boyut ve mertebelerden türev alma işlemleri peridinamik sayısal türev alma metodu kullanılarak elde edilmitşir. Alınan türevler bulanık mantık sisteminde değerlendiriltikten sonra görüntünün RGB ve HSV skalaları üzerinde üç temel dalga boyu dönüşümü yapılmıştır. Bulanık mantık çıktısı üzerine tatbik edilen en etkin üç dalga boyu ile ortak noktaların tespiti gerçekleştirilerek ray kusurlarının daha belirgin bir şekilde ortaya çıkması sağlanmıştır. Ayrıca üç farklı tam spektrum örnek ray kusur görüntüsü ile geliştirilen algoritma test edilip, literatürdeki mevcut kenar bulma algoritmalarına göre daha iyi sonuç verdiği tespit edilmiştir.

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Cite This Article

MIZRAK, C. (2022). Detection of Rail Surface Defects by Full Spectrum Image Processing with the Help of Peridynamic Based Fuzzy Logic Algorithm. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, Cilt: 9 - Sayı: 1, 16–27. https://ajindex.com/articles/493917

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