국부 이진 패턴 분석에 기초한 지절 결함 검출 시스템 구현 = Implementation of Paper Cutting Defect Detection System Based on Local Binary Pattern Analysis

다국어 초록 (Multilingual Abstract)

Paper manufacturing industries have huge facilities with automatic equipments. Especially, in order to improve the efficiency of the paper manufacturing processes, it is necessary to detect the paper cutting defect effectively and to classify the causes correctly. In this paper, we review the problems of web monitoring system and web inspection system that have been traditionally used in industries for defect detection. Then we propose a novel paper cutting defect detection method based on the local binary pattern analysis and its implementation to mitigate the practical problems in industry environment. The proposed algorithm classifies the defects into edge-type and region-type and then it is shown that the proposed system works stably on the real paper cutting defect detection system.

참고문헌 (Reference)

1 김진수, "참조영상 기반의 COF 결함 검출 및 분류 시스템" 한국정보통신학회 17 (17): 1899-1907, 2013

2 G.Zhao, "Dynamic texture recognition using local binary patterns with an application to facial expressions" 1-14, 2007

3 Viconsys, "Development of monitoring, analysis and detection system of paper machine using new camera application techniques" 2011

4 "Development of low-cost defect monitoring and detecting system of paper cutting for improving production efficiency" GIsystem Co 2010

5 "Current state and prospect of paper industry" KDB 62-81, 2010

6 D.H. Ballard, "Computer vision" Prentice-Hall 1982

7 "Commercialization of real-time polymer, defect detection imbedded system using local binary pattern analysis" Netcustomized Co 2012

8 Jae Y. Lee, "Automatic detection of region-mura defect in TFT-LCD" 87-D (87-D): 2371-2378, 2004

9 M.heikkila, "A Texture-based method for detecting moving objects" 2004