Surface Defect Detection and Quantification with Image Processing Methods (Theoretical Investigations and Applied Studies in Engineering)
Yazarlar (1)
Prof. Dr. Turgut ÖZSEVEN Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Bölüm Adı | Surface Defect Detection and Quantification with Image Processing Methods | ||
| Kitap Adı | Theoretical Investigations and Applied Studies in Engineering | ||
| Bölüm Sayfaları | 63-98 | ||
| Kitap Türü | Kitap Bölümü | ||
| Kitap Alt Türü | Alanında ulusal yayınlanan kitap bölümü | ||
| Kitap Niteliği | Alanında tanınmış ulusal bir yayınevince basılan bilimsel kitap | ||
| Kitap Dili | İngilizce | Basım Tarihi | 01-2019 |
| DOI Numarası | – | ISBN | 978-605-327-856-6 |
| Basıldığı Ülke | Türkiye | Basıldığı Şehir | Bursa |
| UAK Araştırma Alanları |
Makine Öğrenmesi
|
||
| Özet |
| Quality control is important in the industry and its importance increases with each passing year. In today's industry, the defect of the products produced can create very important problems in terms of both the customer and the subsequent processes of production. Surface Defect Detection (SDD) is an important part of industry quality control. The main purpose is to prevent the defective products containing defects such as cracks, smudges, broken points on the surfaces and prevent them from reaching the customers [1]. Quality control therefore creates an important feedback loop that has a potential impact on manufacturing as well as design, process planning and logistics for all businesses. SDD's manual control has many disadvantages, such as subjectivity, variable standards, and high costs [2]. Until recently, this process was carried out manually. Manual control can be subjective because it depends on many factors such as employee experience and motivation. Fine defects appearing on a low-contrast surface cannot be visibly defined even with a well-trained inspector [3]. Therefore, the development of automation systems which are not affected by working time, fatigue and stress can objectively carry out this process [4],[5]. Automated control systems using image processing can overcome most of the disadvantages of manual control and offer manufacturers the opportunity to significantly improve quality and reduce costs [2]. |
| Anahtar Kelimeler |
