• Journal of Veterinary Clinics
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• v.13 no.2
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• pp.140-143
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• 1996

In this paper the development of an automatic body temperature measuring system which can be attached to the milking machine has been studied. Since the disease is highly related to the body temperature of the cattle, early detection of the abnormal temperature would prevent the severe problems which may occur in dairy farms. The electronic component AD590 is used as a temperature sensor for the system. The device is highly robust against the noise since the output signal is the current. So it can be applied to the long distance sensing. The resolution of the signal is $0.1{\circ}C$ and the current is 10 mV. Also the A/D converter is designed for interfacing the sensor with a computer. A temperature measuring experiment using the developed system has been done for measuring the temperature of human beings and the system was proven to be useful for measuring the body temperature of the dairy cattle properly.

• Journal of Korea Multimedia Society
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• v.21 no.6
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• pp.659-666
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• 2018

The classification of the tablets recovered according to prescription changes is usually carried out manually by a number of pharmacists at the hospitals. Relatively high-wage pharmacists carry out the reclassification of the tablets, which results in a large loss of time and labor, and if the tablets are incorrectly classified, this can lead to medical accidents. In order to overcome these problems, a new automatic tablet classifying machine has been introduced. In the conventional automatic tablet classifying machine, tablets having various shapes, sizes, and colors are transferred to a classifying machine through the line feeder. Problems such as breakaway of the tablets from the line feeder, pilling of the tablets in the line feeder, and appearance contamination of the tablets occur. In this paper, we propose a system that automatically classifies the shape, size, and color of tablets through individual supply method by vacuum adsorption and image processing.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.132-135
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• 2004

Building information plays a key role in diverse applications such as urban planning, telecommunication and environment monitoring. Automatic building extraction has been a prime interest in the field of GIS and photogrammetry. In this paper, we presented an automatic approach for building extraction from lidar data. The proposed approach is divided into four processes: pre-processing, filtering, segmentation and building extraction. Experimental results showed that the proposed method detected most of buildings with less commission and omission errors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.729-733
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• 1997

Due to the variety of disturbance, it is not ease to accomplish the in-process detection of weld line with non-contact sensor. To get around this difficulties problem develop an automatic seam tracking weld system, the reliable signal processing algorithm has been recommanded. In this research, laser displacement sensor is applied as a seam finder in the automatic tracking system. The sensor is controlled by a dc servo motor which is mounted at X-Y moving table. X-Y moving table manipulated by an ac servo motor controls the position and velocity of the welding torch. First, X-Y table moves to Y-axis to search the welding joint feature before starting the welding, and welding joint is from the scanning data and weighting factor for each other. Second, weld line is determined using proposed signal processing algorithm during welding process. Form the experimental results, we could see the possibility that laser displacement sensor with procesed algorithm can be used as a seam finder in welding process under the severe noise (spatter,arc light etc.) condition

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.72-79
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• 1995

The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurment of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easily illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is 0 in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed automatic inspection system can be applied in real situation.

• Speech Sciences
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• v.11 no.2
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• pp.217-226
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• 2004

An automatic pronunciation correction system provides users with correction guidelines for each pronunciation error. For this purpose, we develop a speech recognition system which automatically classifies pronunciation errors when Koreans speak a foreign language. In this paper, we propose a machine scoring method for automatic assessment of pronunciation quality by the speech recognizer. Scores obtained from an expert human listener are used as the reference to evaluate the different machine scores and to provide targets when training some of algorithms. We use a log-likelihood score and a normalized log-likelihood score as machine scoring methods. Experimental results show that the normalized log-likelihood score had higher correlation with human scores than that obtained using the log-likelihood score.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.10
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• pp.28-34
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• 1997

This paper describes an automatic measurement method for the in-line inspection of assembly tolerances of cathod ray electron guns. The method uses an optical microscope with a CCD camera as a probe. An automatic gap recognition algorthm with digital image processing and a new software autofocus algorithm based on using an optimal edge detector have been developed to improve the measuring accuracy. An inspection system has been proposed and practically implemented for in-line inspection to a real factory automation line. The inspection system consists of a gap inspection part and an eyelet. Total time consumed for inspecting all measuring items is about 10 seconds and the repeatability is below .+-. 5 .mu. m

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1206-1213
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• 2006

Fast detection and automatic generation of worm signatures are essential to contain zero-day worms because the speed of self-propagating worms is too fast for humans to respond. In this paper, we propose an automatic signature generation method against worm's attack, and show the effectiveness of the proposed method by implementing it and appling it to the DHT based network and generating the worm signatures for it.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.177-183
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• 2022

To measure the size and weight of the fish, we developed an automatic fish size measurement system using a deep neural network, where the YOLO (You Only Look Once)v3 model was used. To detect fish, an IP camera with infrared function was installed over the fish pool to acquire image data and used as input data for the deep neural network. Using the bounding box information generated as a result of detecting the fish and the structure for which the actual length is known, the size of the fish can be obtained. A GUI (Graphical User Interface) program was implemented using LabVIEW and RTSP (Real-Time Streaming protocol). The automatic fish size measurement system shows the results and stores them in a database for future work.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.