Scopus
Machine vision based defect detection approach using image processing
IDAP 2017 - International Artificial Intelligence and Data Processing Symposium · Ekim 2017
Makale Bilgileri
DergiIDAP 2017 - International Artificial Intelligence and Data Processing Symposium
Yayın TarihiEkim 2017
Scopus ID2-s2.0-85039896936
Özet
Machine vision systems are used in industrial production areas to produce products with fast, perfect and high precision. These systems allow users to make highly accurate and non-contact measurements and can detect deficiencies in the production process. In this work, a machine vision based non-contact defect detection algorithm for printed circuit boards (PCBs) has been developed. In this approach, which detects and controls the holes on the PCB, first a reference image is taken from the system and feature extraction process is applied to this image. In this real-time working approach, the reference image is matched with the incoming test images and the missing holes on the PCB are precisely detected. Furthermore, it has been determined that the error amount is less than 2 μM in experimental studies. This approach, which works independently of color, position and direction, enables the defect detection process to be done very quickly and precisely.
Yazarlar (4)
1
Mehmet Baygin
2
Mehmet Karaköse
3
Alisan Sarimaden
4
Erhan Akin
ORCID: 0000-0001-6476-9255
Anahtar Kelimeler
Counting
Defect detection
Image processing
Machine vision
PCB
Kurumlar
Ardahan Üniversitesi
Ardahan Turkey
Firat Üniversitesi
Elazig Turkey
Metrikler
58
Atıf
4
Yazar
5
Anahtar Kelime