An approach for automated defect detection and neural classification of web textile fabric

• Autorzy: Stojanovic R. , Mitropulos P. , Koulamas C. , Karayiannis Y. , Koubias S. , Papadopoulos G.
• Języki publikacji: EN

Abstrakty

EN

This paper presents an automatic vision-based system for quality control of web textile fabrics. A general hardware and software platform developed to solve this problem is presented and a powerful algorithm for defect inspection is proposed. Based on the improved binary, textural and neural network algorithms, the proposed method gives good results in detection of many types of fabric defects under real industrial conditions, where presence of many types of noise is an inevitable phenomenon. A high detection rate with good localization accurancy, low rate of false alarms, compatibility with standard inspection tools and low price are the main advantages of proposed system, as well as of the overall inspection approach.

Słowa kluczowe

EN

automated visual inspection; textile fabric; defect detection; texture analysis; neural classification

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2000
• Tom: Vol. 9, No. 3
• Strony: 587--607
• Opis fizyczny: Bibliogr. 35 poz.

Twórcy

autor

Stojanovic R.

autor

Mitropulos P.

autor

Koulamas C.

autor

Karayiannis Y.

autor

Koubias S.

autor

Papadopoulos G.

• Applied Electronics Laboratory, VLSI Laboratory Departament of Electrical and Computer Engineering University of Patras, Greece,