• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2453-2455
• /
• 2003

We propose a path planning method to reduce the inspection time of AOI (automatic optical inspection) machines in SMT (surface mount technology) in-line system. Inspection windows of board should be clustered to consider the FOV (field-of-view) of camera. The number of clusters is desirable to be minimized in order to reduce the overall inspection time. We newly propose a genetic algorithm to minimize the number of clusters for a given board. Comparative simulation results are presented to verify the usefulness of proposed algorithm.

• The Optical Journal
• /
• s.154
• /
• pp.46-56
• /
• 2014

• JOURNAL OF ELECTRICAL WORLD
• /
• no.2 s.146
• /
• pp.11-18
• /
• 1989

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1998.12a
• /
• pp.401-406
• /
• 1998

• Proceedings of the Korean Nuclear Society Conference
• /
• 2005.10a
• /
• pp.723-724
• /
• 2005

• Journal of Convergence for Information Technology
• /
• v.9 no.3
• /
• pp.8-15
• /
• 2019

Recently, the importance of pre-shipment quality inspection has been emphasized due to the increase of STB supply. In this paper, we propose a method to support automation of quality inspection through simultaneous multi-channel input of STB video signal. The proposed method extracts a fingerprint using the center scan line of the image after stable video shot boundary detection using CeLDP combining color information and LDP code and performs synchronization between input video channels. The proposed method shows stronger shot boundary detection performance than the conventional shot detection method. Through the experiments applied to the real environment, it is possible to secure reliability and real-time quality check for synchronization between multi-channel inputs required for STB quality inspection. Also, based on the proposed method, we intend to study a large-scale quality inspection method in the future and propose a more effective quality inspection system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.1
• /
• pp.28-36
• /
• 2020

In shipbuilding industry, there is conducting most of works by welding at the shipyard, and the volume of welding is increasing with international trends of green ships. Welding joint is guaranteed quality through non-destructive testing (NDT). The manual welding inspection report is produced by identifying the drawings designed, which results in losses the many workforce and occurs human errors. To solve these problems, this paper covers a system that reports on inspection information is automatically generation by input data based on shipbuilding-specific CAD. The developed system analyzes the shape data from drawings of modeling. Also, the system determines welding joints through expansion of the part boundary and generates tag numbers. In addition, it provides the function to automatically extract the information needed for inspection such as weld length, thickness and etc. We conducted test to verify the usefulness of the developed system and confirmed that the welding inspection information extracted through system matches the information shown in drawings of modeling.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1131-1135
• /
• 2005

Since human is vulnerable to emotional, physical and environmental distractions, most human inspectors cannot sustain a consistent 8-hour inspection in a day specifically for small components like door locking levers. As an alternative for human inspection, presented in this study is the development of a machine vision inspection system (MVIS) purposely for door locking levers. Comprises the development is the structure of the MVIS components, designed to meet the demands, features and specifications of door locking lever manufacturing companies in increasing their production throughput upon keeping the quality assured. This computer-based MVIS is designed to perform quality measures of detecting missing portions and defects like burr on every door locking lever. NI Vision Builder software for Automatic Inspection (AI) is found to be the optimum solution in configuring the needed quality measures. The proposed software has measurement techniques such as edge detecting and pattern-matching which are capable of gauging, detecting missing portion and checking alignment. Furthermore, this study exemplifies the incorporation of the optimized NI Builder inspection environment to the pre-inspection and post-inspection subsystems.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.10
• /
• pp.1030-1035
• /
• 2014

Machine vision inspection systems have replaced human inspectors in defect inspection fields for several decades. However, the inspection results of machine vision are often affected by small changes of illumination. When small changes of illumination appear in image histograms, the influence of illumination can be decreased by transformation of the histogram. In this paper, we propose an enhanced histogram matching algorithm which corrects distorted histograms by variations of illumination. We use the resolution resizing method for an optimal matching of input and reference histograms and reduction of quantization errors from the digitizing process. The proposed algorithm aims not only for improvement of the accuracy of defect detection, but also robustness against variations of illumination in machine vision inspection. The experimental results show that the proposed method maintains uniform inspection error rates under dramatic illumination changes whereas the conventional inspection method reveals inconsistent inspection results in the same illumination conditions.

• Journal of Industrial Technology
• /
• v.21 no.B
• /
• pp.67-74
• /
• 2001

According as the patterns of PCB (Printed Circuit Board) become denser and complicated, quality and accuracy of PCB influence the performance of final product. It's attempted to obtain trust of 100% about all of parts. Because human inspection in mass-production manufacturing facilities are both time-consuming and very expensive, the automation of visual inspection has been attempted for many years. Thus, automatic visual inspection of PCB is required. In this paper, we used an algorithm which compares the reference PCB patterns and the input PCB patterns are separated an object and a scene by filtering and edge detection. And than compare two image using pattern matching algorithm. We suggest an defect inspection algorithm in PCB pattern, to be satisfied low cost, high speed, high performance and flexibility on the basis of $640{\times}480$ binary pattern.