• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.852-861
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• 2013

When users use medical volume rendering applications, selecting specific region of volume data and observing the region by magnification is a common process.As the wood-grain artifact is arise from the magnified image, the jittered sampling technique has been used to remove the problem. However, the jittered sampling leads to some noise along the volume edge. In this research, we reveal the reason of the noise, and present a solution. To remove the wood-grain artifact without the noise, we propose the empty space jittering and the sampling alignment method. Using these methods, we can produce high quality volume rendering images without noticeable time consuming.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.416-419
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• 2003

The cellular neural networks have the circuit structure that differs from the form of general neural network. It consists of an array of the same cell which is a simple processing element, and each of the cells has local connectivity and space invariant template property. In this paper, time-multiplex image processing technique is applied for processing large images using small size CNN cell block, and we simulate the edge detection of a large image using the simulator implemented with a c program and matlab model. A 5$\times$5 CNN hardware and pre post processor is also implemented and is under test.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.754-757
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• 2003

In Oriental medicine, the shape of collarette that formed with position in iris of patients often used by health diagnotcian to grasp health condition. In this paper, we present method that effectively extract collarette that exist in Iris image. After proposed method detert iris area using circular edge detector, derides boundary candidate point through radial line search and threshold value establishment. And boundary candidate line is treated to use nearest neighbor calculation at each boundary candidate point, finally extracts collarette through linear interpolation. As a result of experimenting about iris images, We Confirmed that can be used as assistant tool of diagnostic system that can presume state of ventriculus of human body.

• Journal of IKEEE
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• v.24 no.3
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• pp.685-690
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• 2020

We propose an efficient convolutional neural network with much lower computational complexity and higher accuracy based on MobileNet V2 for mobile or edge devices. The proposed network consists of bottleneck layers with larger expansion factors and adjusted number of channels, and excludes a few layers, and therefore, the computational complexity is reduced by half. The performance the proposed network is verified by measuring the accuracy and execution times by CPU and GPU using ImageNet100 dataset. In addition, the execution time on GPU depends on the CNN architecture.

• Journal of the Korean Society of Combustion
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• v.20 no.1
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• pp.24-31
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• 2015

Flame structure, which contains a useful information for studying combustion instability of the flame, is often quantitatively visualized with PLIF (planar laser-induced fluorescence) and/or chemiluminescence images. The latter, a line-integral of a flame property, needs to be preprocessed before being inverted, mainly due to its inherent noise and the axisymmetry assumption of the inversion. A preprocessing scheme utilizing multi-division of ROI (region of interest) of the chemiluminescence image is proposed. Its feasibility has been tested with OH PLIF and $OH^*$ chemiluminescence images of SNG (synthetic natural gas) swirl-stabilized flames taken from a model gas turbine combustor. It turns out that the multi-division technique outperforms two conventional ones: those are, one without preprocessing and the other with uni-division preprocessing, reconstructing the SNG flame structure much better than its two counterparts, when compared with the corresponding OH PLIF images. It is also found that the Canny edge detection algorithm used for detecting edges in the multi-division method works better than the Sobel algorithm does.

• Korean Journal of Digital Imaging in Medicine
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• v.11 no.2
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• pp.109-114
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• 2009

Carried out an experiment for quantitative evaluation about intraoral sensor among oral dental imaging equipments in PACS environment. For evaluation, testing environment & evaluation criteria are established that refer to the 'IEC 62220-1-2' and experimented with set up the standard radiation penetration that correspond with RQA-3(IEC 61267). Results of experiments using the image J, derived the ESF(edge spread function), LSF (line spread function) and calculated the MTF(modulation transfer function) finally. As a result, the MTF that 0.1, 0.2sec are 10% about 10 lp/mm and 0.32 sec is the 10% about 9 lp/mm in level represents the value of the MTF. Change of scan condition in dental environmental, according to the MTF value taken note that no changes can be seen enough. However, the dimensions of each other size $1(1200{\times}1600)$, size $2(1440{\times}1920)$ intraoral sensors for 3 lp/mm, respectively 40%, 90% of the note might have been the difference between the value of MTF, in accordance with standard sensors might note differences could be observed.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.11 s.242
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• pp.1182-1188
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• 2005

An x-ray PIV (Particle Image Velocimetry) technique was developed to measure quantitative information on flows inside opaque conduits and on opaque-fluid flows. At first, the developed x-ray PIV technique was applied to flow in an opaque Teflon tube. To acquire x-ray images suitable for PIV velocity field measurements, refraction-based edge enhancement mechanism was employed using detectable tracer particles. The optimal distance between with the sample and detector was experimentally determined. The resulting amassed velocity field data were in reasonable agreement with the theoretical prediction. The x-ray PIV technique was also applied to blood flow in a microchannel. The flow pattern of blood was visualifed by enhancing the diffraction/interference -bas ed characteristic s of blood cells on synchrotron x-rays without any contrast agent or tracer particles. That is, the flow-pattern image of blood was achieved by optimizing the sample (blood) to detector distance and the sample thickness. Quantitative velocity field information was obtained by applying PIV algorithm to the enhanced x-ray flow images. The measured velocity field data show a typical flow structure of flow in a macro-scale channel.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.71-76
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• 2007

Object detection process which makes decision on the existence of meaningful objects in a given image is a crucial part of image recognition in computer vision system. Hausdorff distance metric has been used in object detection and shows good results in applications such as face recognition. It defines the dissimilarity between two sets of points and is used to find the object that is most similar to the given model. This paper proposes a Hausdorff distance based detection method that uses directional information of points to improve detection accuracy when the sets of points are derived from edge extraction as is in usual cases. In this method, elastic energy needed to make two directional points coincident is used as a measure of similarity.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.37-43
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• 2003

The purpose of this thesis is to detect multiple vehicles using sequence image analysis at process that detect forward vehicles and lane from sequential color images. Detection of vehicles candidate area uses shadow characteristic and edge information in one frame. And, method to detect multiple vehicles area analyzes Estimation of Vehicle(EOV) and Accumulated Similarity Function(ASF) of vehicles candidate areas that exist in sequential images and examine possibility to be vehicles. Most researches detected a forward vehicles in road images but this research presented method to detect several vehicles and apply enough in havy traffic. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and present the results such as processing time, accuracy and vehicles detection in the images.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.365-372
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• 1996

The researches to acquire diagnostic parameters from ultrasonic images are advanced with the progress of the digital image processing technique. Especially, the detection of endocardial boundary is very important in ultrasonic images, because endocardial boundary is used as a clinical parameter to estimate both the cardiac area and the variation of cardiac volume. Various methods to detect cardiac boundary are proposed, but these are insufficient to detect boundary. In this paper, an algorithm that detects the endocardial boundary, expanding the cavity region from the center using statistical information, is proposed The value of mean and sty:nd, wd deviation in cavity region is lower than those in muscle re- gion. Therefore, if we define the multiplication of mean and standard deviation as homogeneous coefficient, it can lead to conclusion that the pixels with small variation of these coefficleno are cavity region, and extraction of endocardial boundary from cavity region is possible. The proposed method detected endocardial boundary more effectively than edge based or threshold based method and is robuster to noise than radial searching method that has high dependency for center position.