• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.127-135
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• 2004

With the wide-spread use of multimedia technology, the demand for the image processing engineer is increasing in various fields. But there are few engineers who can develop practical applications in the image processing area. To teach practical image processing techniques, we need an integrated education environment which can efficiently present the image processing theory and, at the same time, provide interactive experiments for the theory presented. In this paper, we propose an integrated education environment for the image processing, which is called MTES. It consists of the theory presentation systems and the experiment systems. The theory presentation systems support multimedia data, web document and Microsoft Powerpoint$^{TM}$ file. It is tightly integrated with the experiment systems which are developed based on the integrated image processing algorithm development system, called Hello-Vision.n.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.780-791
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• 1996

A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.319-322
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pass- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this Prediction system was acquired ${\pm}$3.2% error range.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.178-184
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• 2004

In this paper, we designed an image processing system for the high speed line-scan camera which adopts the new memory model we proposed. As a resolution and a data rate of the line-scan camera are becoming higher, the faster image processing systems are needed. But many conventional systems are not sufficient to process the image data from the line-scan camera during a very short time. We designed the memory controller which eliminates the time for transferring image data from the line-scan camera to the main memory with high-speed SRAM and has a dual-port configuration therefore the DSP can access the main memory even though the memory controller are writing the image data. The memory controller is implemented by VHDL and Xilinx SPARTAN-IIE FPGA.

• Journal of Oral Medicine and Pain
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• v.21 no.1
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• pp.37-54
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• 1996

In this thesis, a new superimposition scheme using a computer vision system was proposed with 7 pairs of skull and ante-mortem photographs, which were already identified through other tests and DNA fingerprints at the Korea National Institute of Scientific Investigation. At this computer vision system, an unidentified skull was caught by video-camcoder with the MPEG and a ante-mortem photograph was scanned by scanner. These two images were processed and superimposed using pixel processing. Recognition of the individual identification by anatomical references was performed on the two superimposed images. These results were as followings. 1. For the enhancement of skull and ante-mortem photographs, various image processing schemes, such as SMOOTH, SHARPEN, EMBOSS, MOSAIC, ENGRAVE, INVERT, NEON and COLOR TO MONO, were applied using 3*5 window processing. As an image processing result of these methods, the optimal techniques were NEON, INVERT and ENGRAVE for the edge detection of skull and ante-mortem photograph. 2. Using various superimposition image processing techniques (SRCOR, SRCAND, SRCINVERT, SRCERASE, DSTINVERT, MERGEPAINT) were compared for the enhancement of image recognition. 3. By means of the video camera, the skull image was inputed directly to a computer system : superimposing it on the ante-mortem photograph made the identification more precise and time-saving. As mentioned above, this image processing techniques for the superimposition of skull and ante-mortem photographs simply used the previous approach, In other wrods, taking skull photographs and developing it to the same size as the ante-mortem photographs. This system using various image processing techniques on computer screen, a more precise and time-saving superimposition technique could be able to be applied in the area of individual identification in forensic practice.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.1
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• pp.1-6
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• 2004

In this paper, we present the new method for joint aspect inspecting system. We use the image processing and laser maker for light source. We can find the matrial joint status through processing the line pattern which is made by laser maker. To get the line pattern, in first, we did the preprocess of threshold. If the shape of line had over two segments, then the joint status is abnormal. We show our system efficency by experiment on tire facility.

• Journal of Animal Environmental Science
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• v.7 no.3
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• pp.177-182
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• 2001

This study was conducted to find out the coefficient relationships between intensity values image processing and pollution density of slurries. Slurry images were obtained from the image processing system using personnel computer and CCD-camera. Software, written in Visual $c^{++}$, combined the functions of the image capture, image processing and image analysis. The data of image processing for slurries were analyzed by the method of regression analysis. The results are as follows. 1. Red(R)-values among image processing data were obtained the highest correlation coefficient 0.9213 for detecting COD. Also, green(G)-value were obtained the highest correlation coefficient 0.9019 fur detecting BOD. Blue(B)-value could not find significant values to detect the pollution resources density. 2. Hue(H)-values among image processing data were obtained the highest correlation coefficient 0.9466 for detecting BOD. This fact could be used in detecting BOD 3. Green(G)-value, GRAY-value, Hue(H)-value, Saturation(5)-value and Intensity(I)-value were the correlation coefficient more than 0.8 for BOD. Hue(H)-value was higher correlation coefficient than any other value. It was possible to detect pollution density of slurries by using the image processing system. 4. Red(R)-value, GRAY-value and Saturation(5)-value were obtained the correlation coefficient more than 0.8 for detecting COD. a-value had the highest correlation coefficient Among these values. It was possible to detect density indirectly by using the image processing system. 5. SS-density were obtained the correlation coefficient less than 0.8 by using the image processing system. The density of $NH_4$-N and $NO_3$-N were obtained correlation coefficient less than 0.2.

• Journal of Animal Environmental Science
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• v.7 no.3
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• pp.183-190
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• 2001

The objective of this research was to design and construct an image processing system to measure easily and accurately cow's weight. The image processing system was built for a dairy cattle to be measured and estimated it's weight using camera and personal computer. The pixel numbers, which was derived from the image processing system, were counted to estimate the weight of a dairy cattle. They were utilized various was for finding the relationships between pixel numbers and it's real weight. Based on the results of this research the following conclusions were made: 1. It's weight could be estimated by using pixel numbers, which was captured from top and side cameras to measure it. The correlations with tea-view pixel numbers, side-view pixel numbers, superficial area pixel numbers and the volume pixel numbers were 0.909, 0.939, 0.944 and 0.965. 2. 50 cattle was used to execute an experiment with the image processing system, but average errors were big to make out the good relationship between cow's weight and pixel numbers. In order measure accurately a cattle weight, cattle weight, cattle groups would be divided by the age of cattle and further study should be carried out to be based on the results of this research. 3. The average time it took to perform the image processing to be measure it was 10 seconds, but it took 10 minutes for cattle to enter for measuring it's weight into the weighting system.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.284-296
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• 2005

Bridge displacement measurement system using image processing is developed to overcome the contact type system inefficiencies such as heavy, expensive property and temporary construction necessity. The system is composed of tablet PC with IEEE1394 digital camera, telescope lens and a designed target mark. The key is projection algorithm where all pixels are added up for each row(column) to find out the center line. The experimental results are shown compared with a contact type system.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.11 no.2
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• pp.52-57
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• 2012

In this paper describe configuration about QCM system for image processing device. It presents that QCM's image processing board video from the camera recognized by the PLC's battery removable exact location coordinates to the robot image processing technology to deliver. In addition, QCM video image processing technology for improved data reliability is described. In this paper define the landmarks of battery for obtaining the location coordinates and verify battery the location coordinates acquisition process from field tests of the QCM/QTPE-BUS Battery Exchange System.