• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.437-439
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• 2006

Actually, The present traffic accident detection system is subsisting limitation of accurate distinction under the crowded condition at intersection because the system defend upon mainly the image information at intersection and digital image processing techniques nearly all. To complement this insufficiency, this article aims to estimate the level of present technology and a realistic possibility by analyzing the acoustic characteristic of crash sound that we have to investigate for improvement of traffic accident detection rate at intersection. The skid sound of traffic accident is showed the special pattern at 1[kHz])${\sim}$3[kHz] bandwidth when vehicles are almost never operated in and around intersection. Also, the frequency bandwidth of vehicle crash sound is showed sound pressure difference oyer 30[dB] higher than when there is no occurrence of traffic accident below 500[Hz].

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.491-494
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• 2004

Neural Oscillator can be applied to oscillatory systems such as the image recognition, the voice recognition, estimate of the weather fluctuation and analysis of geological fluctuation etc in nature and principally, it is used often to pattern recoglition of image information. Conventional BPL(Back-Propagation Learning) and MLNN(Multi Layer Neural Network) are not proper for oscillatory systems because these algorithm complicate Learning structure, have tedious procedures and sluggish convergence problem. However, these problems can be easily solved by using a synchrony characteristic of neural oscillator with PLL(phase-Locked Loop) function and by using a simple Hebbian learning rule. And also, Recognition velocity of Korean Character can be improved by using a Neural Oscillator's learning accelerator factor η$\_$ij/

• Journal of The Korean Association For Science Education
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• v.14 no.2
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• pp.111-122
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• 1994

This study tried to find the effect to the representation patterns of science concepts upon the momentum effect. The previous studies showed that the momentum effect is influenced by students' cognitive levels and the abstractness of test items. The representation patterns of science concepts are divided into 4 different types: quantitative and qualitative, verbal and image. The research method used in this study is time series design. The period is 50 days. The period is divided into "pre-lest", "intervention-test", "post-test". Pre-test period is 5 days and in this period class instruction does not exist. Intervention-lest period is 30 days and in this period class instruction exist. Post-test period is 15 days and in this period class instruction does not exist. The results showed longer momentum effect on the image-qualitative representation pattern than the other representation patterns. Qualitative concepts is formed better than quantitative. Momentum effects is not artifact but the essential characteristics of science study.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.363-371
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• 2014

In this paper, a new super-resolution algorithm is proposed by using successive frames for generating high-resolution frames with better quality than those generated by other conventional interpolation methods. Generally, each frame used for super-resolution must only have global translation and motions of sub-pixel unit to generate good result. However, the newly proposed MSR algorithm in this paper is exempt from such constraints. The proposed algorithm consists of three main processes; motion estimation for image registration, normalization of motion vectors, and pattern analysis of edges. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.

• 한국가시화정보학회:학술대회논문집
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• 2002.11a
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• pp.101-104
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• 2002

Simultaneous measurement of turbulent velocity and concentration field in a stirred mixer tank is carried out by using PIV/LIF technique. Instantaneous velocity fields are measured by a $1K\times1K$ CCD camera adopting the frame straddle method while the concentration fields are obtained by measuring the fluorescence intensity of Rhodamine B tracer excited by the second pulse of Nd:Yag laser light. Image distortion due to the camera view-angle is compensated by a mapping function. It is found that the general features of the mixing pattern are quite dependent on the local flow characteristics during the rapid decay of mean concentration. However, the small scale mixing seems to be independent on the local turbulent velocity fluctuation.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2000.06a
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• pp.54-61
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• 2000

A method and results of classification of 4 types metallic wear debris were presented by using their color features. The color image of wear debris was used (or the initial data, and the color properties of the debris were specified by HSI color model. Particle was characterized by a set of statistical features derived from the distribution of HSI color model components. The initial feature set was optimized by a principal component analysis, and multidimensional scaling procedure was used for the definition of classification plane. It was found that five features, which include mean values of H and S, median S, skewness of distribution of S and I, allow to distinguish copper based alloys, red and dark iron oxides and steel particles. In this work, a method of probabilistic decision-making of class label assignment was proposed, which was based on the analysis of debris-coordinates distribution in the classification plane. The obtained results demonstrated a good availability for the automated wear particle analysis.

• Proceedings of the IEEK Conference
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• summer
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• pp.417-420
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• 2004

Caenorhabditis (C) elegans is often used in genetic analysis in neuroscience because its simple organism; an adult hermaphrodite contains only 302 neuron. So the worm is often used to study of cancer, alzheimer disease, aging, etc. To analysis mutant type of the worm, an experienced observer was able to subjectively before, but requirements for objective analysis are now increasing. For this reason, we use automated tracking systems to extract global movement coordinate of the worm. In this paper, we extract features, which are related on reversal and movement of the worm. Using these features, we quantitatively analysis 6 type mutant by movement and reversal characteristic.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.84-95
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• 2009

The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1372-1381
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• 2017

In this paper, a texture feature extraction method using local energy and local correlation of Gabor transformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known to be similar to the response of the human visual system. The outputs of the Gabor transformation are robust to variants of object size and illumination. Due to such advantages, it has been actively studied in various fields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superior aspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformed images and then applied to an image retrieval system. Some experiments are conducted to compare the performance of the proposed method with those of the conventional Gabor method and the popular rotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. The Mahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to the conventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66% higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB, respectively, than the popular RULBP method.

• Journal of Fashion Business
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• v.23 no.4
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• pp.13-23
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• 2019

This study aims to understand the concept of pixel, the most important factor in constituting a digital image, draw the formative characteristics of pixelation image expressed through non-digital media, and develop fashion design reflecting the characteristics. As a research method, the literature review was conducted in the present study by involving domestic and foreign publications, related academic journals, and theses and dissertations on the pixel and pixelation image based on a qualitative research process. In addition, through an analysis of the cases that borrowed pixelation images in non-digital media like contemporary art and design, etc., an attempt was made to draw the formative characteristics of the pixelation image. Apparently, six fashion design looks are presented in the present study. The formative characteristics of the pixelation image include: first, the repeatability that repeats the minimum unit; second, the incompleteness of the shape appearing through the phenomenon of aliasing due to the characteristics of the pixel; and third, the combination that completes the shape through the combination of individual independent pixels. The results of the expression through reflecting them in fashion design are as follows: first, this study chose one small geometric formative element and presented repeatability by repetitively expressing that element in a textile pattern; second, for incompleteness, this study expressed an incomplete form, handling the edge part of the shape with the method of disentangling the strand; and third, the combination by completing a single look through overlapping of independent textiles and the combination of different independent individuals is expressed.