![](/images/graphics-bg.png)
Integrating the Symmetry Image and Improved Sparse Representation for Railway Fastener Classification and Defect Recognition
المؤلفون المشاركون
Liu, Jiajia
Li, Bailin
Xiong, Ying
He, Biao
Li, Li
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-11-09
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
The detection of fastener defects is an important task for ensuring the safety of railway traffic.
The earlier automatic inspection systems based on computer vision can detect effectively the completely missing fasteners, but they have weaker ability to recognize the partially worn ones.
In this paper, we propose a method for detecting both partly worn and completely missing fasteners, the proposed algorithm exploits the first and second symmetry sample of original testing fastener image and integrates them for improved representation-based fastener recognition.
This scheme is simple and computationally efficient.
The underlying rationales of the scheme are as follows: First, the new virtual symmetrical images really reflect some possible appearance of the fastener; then the integration of two judgments of the symmetrical sample for fastener recognition can somewhat overcome the misclassification problem.
Second, the improved sparse representation method discarding the training samples that are “far” from the test sample and uses a small number of samples that are “near” to the test sample to represent the test sample, so as to perform classification and it is able to reduce the side-effect of the error identification problem of the original fastener image.
The experimental results show that the proposed method outperforms state-of-the-art fastener recognition methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Jiajia& Li, Bailin& Xiong, Ying& He, Biao& Li, Li. 2015. Integrating the Symmetry Image and Improved Sparse Representation for Railway Fastener Classification and Defect Recognition. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073887
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Jiajia…[et al.]. Integrating the Symmetry Image and Improved Sparse Representation for Railway Fastener Classification and Defect Recognition. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1073887
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Jiajia& Li, Bailin& Xiong, Ying& He, Biao& Li, Li. Integrating the Symmetry Image and Improved Sparse Representation for Railway Fastener Classification and Defect Recognition. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073887
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1073887
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
![](/images/kashef-image.png)