• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1266-1268
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• 1996

In this study an automatic roiling-coli labeling system using robot vision system and peripheral mechanism is proposed and implemented, which instead of the manual labor to attach labels Rolling-coils in a steel miil. The binary image process for the image processing is performed with the threshold, and the contour line is converted to the binary gradient which detects the discontinuous variation of brightness of rolling-coils. The moment invariants algorithm proposed by Hu is used to make it easy to recognize even when the position of the center are different from the trained data. The position error compensation algorithm of six degrees of freedom industrial robot manipulator is also developed and the data of the position of the center rolling-coils, which is obtained by floor mount camera, are transfered by asynchronous communication method. Therefore even if the position of center is changed, robot moves to the position of center and performs the labeling work successfully. Therefore, this system can be improved the safety and efficiency.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.496-502
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• 2016

In this paper, we proposed and implemented a GUI-based system to recognize and record measured values of digital instruments in the industrial site through image processing. Unlike the existing vehicle license plate recognition system, the measured values of the measuring instrument are displayed on the LCD screen as digital numbers. So, the proposed system considers the decimal point, a negative sign, light reflected by LCD protective glass, and various disturbance factors. We used blob-labeling technique to recognize the numbers displayed on the LCD screen, the recognized number images were determined as certain numbers through the template matching, and recognized values were recorded in the storage device with measurement time. Therefore, the proposed system in this paper would reduce the burden of writing when recording the measured values of the inside/outside diameter or height of the product in the industrial site, so effective and errorless process management in production process is possible by preventing errors in recording measurements when written by hand.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.199-206
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• 2016

This paper describes a simple routing control system. We propose achieving high-speed data transmission without modifying the data frame configuration. To add a routing control signal, called the "labeling signal" in this paper, to the data frame, we use a frequency modulation technique on the transmitted frame. This means you need not change the data frame when you transmit additional signals. Using a prototype system comprising a field-programmable gate array and discrete elements, we investigate the system performance and devise a method to achieve high resolution. A three-channel routing control for a 10 Gb/s data frame was achieved, which confirms the advantages of the proposed system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.12
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• pp.1237-1242
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• 2012

No matter how low it might be, noise from home appliances in indoor environment cause displeasure for residents as it is produced nearby. Electronic goods including vacuum cleaner and washing machine generate high frequency noise, which interrupts TV-watching or conversations and cause noises between floors in apartment houses. In particular, refrigerators make constant noise late at night, hampering the study for exams and causing sleeplessness. Korea, despite the government's efforts to promote low-noise goods based on the noise test by corporation, there is a lack of standardization in the test method, test condition and measuring equipments. This is a major reason that lowers the reliability of low-noise products. At present, low-noise home appliances are certified with eco labeling in the nation but, only 7 brands of refrigerators, 4 brands of washing machines and 97 brands of air-conditioners obtained certification as of august, 2011. In addition, none of Kimchi-refrigerator and vacuum cleaner brands were approved as low-noise home appliances. This shows Korea's relatively underdeveloped market for low-noise products, which, in part, is because of the difficulties companies face in being certified with eco labeling as they should satisfy various requirements such as power-saving and eco-friendly design besides low-noise features. As a result, low-noise labeling for home appliances should be established for the revised noise and vibration management law and the study was carried out to establish low-noise labeling system for major noise sources including vacuum cleaner, washing machine, air-conditioner and refrigerator.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.466-471
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• 2010

We have proposed a method to detect and track moving ships using position from Radar and image processor. Real-time segmentation of moving regions in image sequences is a fundamental step in the radar-camera integrated system. Algorithms for segmentation of objects are implemented by composing of background subtraction, morphologic operation, connected components labeling, region growing, and minimum enclosing rectangle. Once the moving objects are detected, tracking is only performed upon pixels labeled as foreground with reduced additional computational burdens.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.189-196
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• 2024

Frequent false positives alarm from the Intelligent Selective Control System have raised significant concerns. These persistent issues have led to declines in operational efficiency and market credibility among agents. Developing a new model or replacing the existing one to mitigate false positives alarm entails substantial opportunity costs; hence, improving the quality of the training dataset is pragmatic. However, smaller organizations face challenges with inadequate capabilities in dataset collection and refinement. This paper proposes an automatic human pose data collection system centered around a human pose estimation model, utilizing camera-based sensor fusion techniques and edge devices. The system facilitates the direct collection and real-time processing of field data at the network periphery, distributing the computational load that typically centralizes. Additionally, by directly labeling field data, it aids in constructing new training datasets.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.25-34
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• 2015

Recently, in distribution market, demand for electronic shelf label system is increasing gradually to provide the accurate price immediately and detailed product information to consumers and reduce operation costs. Most of electronic shelf label system companies develop the full-graphic display device to display a wide variety of product information as well as the exact price. Our system had introduced Go-Back-N retransmission method in the early. However, we encountered performance problems that it delayed updating of the electronic shelf label system and exhausted the battery life time. Proposed adaptive image retransmission technique based on the selective scheme is that tags of electronic shelf label system recognize idle time of transmission cycle and require partial image retransmission to sever by itself. As a result, it can acquire much more opportunities of partial image retransmission within the same period and increase reception rate of full image for each tags. The experimental result shows that adaptive image retransmission technique's reception rate of full image for each tags is approximately 4% higher than existing previous works. And total battery life time increases 30 hours because tag reduce wake-up time as it receive only lost data instead of whole data.

• Journal of IKEEE
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• v.26 no.4
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• pp.647-652
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• 2022

In this paper, we propose a prediction system for skin pore labeling based on a CNN(Convolution Neural Network) model, where a data set is constructed by processing skin images taken by users, and a pore feature image is generated by the proposed image processing algorithm. The skin image data set was labeled for pore characteristics based on the visual classification criteria of skin beauty experts. The proposed image processing algorithm was applied to generate pore feature images from skin images and to train a CNN model that predicts pore feature ratings. The prediction results with pore features by the proposed CNN model is similar to experts visual classification results, where less learning time and higher prediction results were obtained than the results by the comparison model (Resnet-50). In this paper, we describe the proposed image processing algorithm and CNN model, the results of the prediction system and future research plans.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.14
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• pp.75-102
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• 2000

At present, on increasing to use a computer network and internet network, Internet Trade has been rapidly created and developed in international Electronic Commerce. However, Internet Trade has not been continued to grow up without supporting by a efficient Logistics System. Because it is very important to delivery contract commodities to consumer with speedy, accurate, steady, convenient services. International Logistics System is consisted of demand forecasting, order processing, packing, labeling, shipping documentation and consumer service into three distant phases of transaction, distribution and payment. International Logistics System can be done more efficiently and effectively by using Internet Logistics System. Therefore it is very important to implementing a efficient Internet Logistics System.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.9-16
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• 2010

Moving object detection is to detect foreground object different from background scene in a new incoming image frame and is an essential ingredient process in some image processing applications such as intelligent visual surveillance, HCI, object-based video compression and etc. Most of previous object detection algorithms are still computationally heavy so that it is difficult to develop real-time multi-channel moving object detection in a workstation or even one-channel real-time moving object detection in an embedded system using them. Foreground mask correction necessary for a more precise object detection is usually accomplished using morphological operations like opening and closing. Morphological operations are not computationally cheap and moreover, they are difficult to be rendered to run simultaneously with the subsequent connected component labeling routine since they need quite different type of processing from what the connected component labeling does. In this paper, we first devise a fast and precise foreground mask correction algorithm, "Neighbor Foreground Pixel Propagation (NFPP)" which utilizes neighbor pixel checking employed in the connected component labeling. Next, we propose a novel moving object detection method based on the devised foreground mask correction algorithm, NFPP where the connected component labeling routine can be executed simultaneously with the foreground mask correction. Through experiments, it is verified that the proposed moving object detection method shows more precise object detection and more than 4 times faster processing speed for a image frame and videos in the given the experiments than the previous moving object detection method using morphological operations.