• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.983-986
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• 2007

Concrete surface grinding is required for flatness and adhesiveness of concrete surface. The procedure is, however, labor intensive and has a hazardous work condition. Also, the productivity and the quality of concrete surface grinding depend on the levels of worker. Thus, the development of remote controlled concrete surface grinding equipment is necessary to prevent the environmental pollution and to protect the workers from hazardous work condition. However, it is difficult to evaluate the grinded surface objectively in a remote controlled system. The machine vision system developed in this study takes the images of grinded surface with the network camera for image processing. Then, by representing the quality test results to the graphic MMI program of the remote control station, the quality control system is constructed. The machine vision algorithm means the image processing algorithm of grinded concrete surface and this paper presents the objective quality control standard of grinded concrete surface through the application of the suggested algorithm.

• The monthly packaging world
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• s.258
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• pp.96-99
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• 2014

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1559-1564
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• 2011

This study presents the development of a machine vision inspection system(MVIS) purposely for car seat frames as an alternative for human inspection. The proposed MVIS is designed to meet the demands, features and specifications of car seat frame manufacturing companies in striving for increased throughput of better quality. This computer-based MVIS is designed to perform quality measures by detecting holes, nuts and welding spots on every car seat frame in real time. In this study, the NI Vision Builder software for Automatic Inspection was used as a solution in configuring the aimed quality measurements. The techniques for visual inspection are optimized through qualitative analysis and simulation of human tolerance on inspecting car seat frames. Furthermore, this study exemplifies the incorporation of the optimized vision inspection environment to the pre-inspection and post-inspection subsystems. The system built on this proposed MVIS for car seat frames has successfully found the possible detections.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.738-747
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• 2021

Today, with the improvement of deep learning technology, computer vision areas such as image classification, object detection, object segmentation, and object tracking have shown remarkable improvements. Various applications such as intelligent surveillance, robots, Internet of Things, and autonomous vehicles in combination with deep learning technology are being applied to actual industries. Accordingly, the requirement of an efficient compression method for video data is necessary for machine consumption as well as for human consumption. In this paper, we propose an object-based compression of thermal infrared images for machine vision. The input image is divided into object and background parts based on the object detection results to achieve efficient image compression and high neural network performance. The separated images are encoded in different compression ratios. The experimental result shows that the proposed method has superior compression efficiency with a maximum BD-rate value of -19.83% to the whole image compression done with VVC.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.273-282
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• 2022

MPEG-VCM(Video Coding for Machine) aims to standardize video codec for machines. VCM provides data sets and anchors, which provide reference data for comparison, for several machine vision tasks including object detection, object segmentation, and object tracking. The evaluation template can be used to compare compression and machine vision task performance between anchor data and various proposed video codecs. However, performance comparison is carried out separately for each machine vision task, and information related to performance evaluation of multiple machine vision tasks on a single bitstream is not provided currently. In this paper, we propose a performance evaluation method of a video codec for AI-based multi-tasks. Based on bits per pixel (BPP), which is the measure of a single bitstream size, and mean average precision(mAP), which is the accuracy measure of each task, we define three criteria for multi-task performance evaluation such as arithmetic average, weighted average, and harmonic average, and to calculate the multi-tasks performance results based on the mAP values. In addition, as the dynamic range of mAP may very different from task to task, performance results for multi-tasks are calculated and evaluated based on the normalized mAP in order to prevent a problem that would be happened because of the dynamic range.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.209-212
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• 2018

Anisotropic conductive film(ACF) bonding is widely used for making fine interconnections between two different materials where soldering is not easily applicable. There are three constraints for the successful implementation of ACF bonding. A bonding contact should be pressed by a hot head with the right pressure and temperature for a pre-defined curing time. In this paper, a method for ACF bonding based on machine vision system is proposed and verified through some experiments. The system calculates the position and orientation of printed circuit boards(PCBs) on a bonding table and estimates the optimal hitting point where the hot head should be applied. Experimental results show that the proposed system achieves better adhesive strength by providing head flatness over contact surfaces.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.49-56
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• 2014

Generally, the tool presetter is utilized to align and measure some specific dimensions of a machine tool. It is classified into two types(contact and contactless) according to the measurement method, and the optical sensor based contactless scheme has the advantages of measurement flexibility and convenience. This paper describes the design and realization of an industrial tool presetter using machine vision and linear scaler. Before measurement, the objective tool is attached to the mechanical mount and is aligned with the optical apparatus. After capturing tool images, the suggested image processing algorithm calculates its dimesions accurately, combining the traversing distance from the linear scaler. Experimental results conforms that the present tool presetter system has the precision within ${\pm}20um$ error.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.84-90
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• 2004

Today, automobile world market is highly competitive. In order to strengthen the competitiveness, quality of automobile is recognized as important and efforts are being made to improve the quality of manufactured components. The directional ability of automobile has influence on driver directly and hence it must be solved on the preferential basis. In the present research, an automated vision system has been developed to inspect the front chassis module. To interpret the inspection data obtained for front chassis module, new interpreting algorithm have been developed. Previously the control of tolerance of front chassis module was done manually. With the help of the new algorithm developed, the dimension is calculated automatically to check whether the front chassis module is within the tolerance limit or not.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.125-130
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• 2013

In this paper, in order to overcome shortcomings of manual inspection for the automotive PWM Shaft, we developed an automated inline inspection system. The automated inline inspection system consists of the work feeder unit, conveying unit, outer diameter check unit, run-out and roundness check unit, machine vision, defective separation unit and status alarm unit. We used the machine vision system for automatic inspection process and designed the inline systems for automatic feeding and selecting process. Also the repeated operation test was performed in order to verify the precision and reliability of the proposed automated inline inspection system.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.3
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• pp.71-78
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• 1999

This paper presents an integrated and automated inspection system using image processing technology for the automotive engine assembly process. The system make it possible for the inspected data to be entered directly from the machine vision into the statistical process control system. Such direct entry enables the prompt preparation of corrective actions against process problems. An IVP-150 machine vision board is installed within the PC for image processing, and a template matching technology is implemented to precisely verify quality factors. The developed system showed robustness to the problems of noise, distortion, and orientation.