• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.412-414
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• 2001

In this paper, we describe an real-time facial feature tracker. We only used a general USB PC Camera without a frame grabber. The system has achieved a rate of 8+ frames/second without any low-level library support. It tracks pupils, nostrils and corners of the lip. The signal from USB Camera is YUV 4:2:0 vertical Format. we converted the signal into RGB color model to display the image and We interpolated V channel of the signal to be used for extracting a facial region. and we analysis 2D blob features in the Y channel, the luminance of the image with geometric restriction to locate each facial feature within the detected facial region. Our method is so simple and intuitive that we can make the system work in real-time.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1095-1102
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• 2014

In this paper, We proposed the approach of GPU and motion vector to analysis the Human activity in real-time surveillance system. The most important part, that is detect blob(human) in the foreground. We use to detect Adaptive Gaussian Mixture, Weighted subtraction image for salient motion and motion vector. And then, We use motion vector for human activity analysis. In this paper, the activities of human recognize and classified such as meta-classes like this {Active, Inactive}, {Position Moving, Fixed Moving}, {Walking, Running}. We created approximately 300 conditions for the simulation. As a result, We showed a high success rate about 86~98%. The results also showed that the high resolution experiment by the proposed GPU-based method was over 10 times faster than the cpu-based method.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.157-160
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• 2011

In this paper, We proposed the method of recognition and analysis of human activites using Motion vector in real-time surveillance system. We employs subtraction image techniques to detect blob(human) in the foreground. When MPEG-4 video recording EPZS(Enhanced Predicted Zonal Search) is detected the values of motion vectors were used. In this paper, the activities of human recognize and classified such as meta-classes like this {Active, Inactive}, {Moving, Non-moving}, {Walking, Running}. Each step was separated using a step-by-step threshold values. We created approximately 150 conditions for the simulation. As a result, We showed a high success rate about 86~98% to distinguish each steps in simulation image.

• Journal of Fashion Business
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• v.7 no.5
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• pp.108-118
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• 2003

Surface properties, including the texture and the luster, of cotton fibers and yarns thereof play an important role in textile technology. The convolutions and the cross-sectional shape of the cotton fiber affect the fabric texture and the luster accordingly. Mercerization of the cotton fabric affects the luster, strength, and other properties of the fabric. In this study, the effect of mercerization was examined on the luster of the cotton fabric, together with the effect of polishing treatment. One of the traditional methods determining the fabric luster is the use of glossmeter or goniometric glossmeter. The use of glossmeter gives successful results in determining the gloss of rather flat and continuous surface such as plastic sheet, painted surface, or paper products. Since the textile fabrics have diverse surface structures and textures, these could be regarded as having three-dimensional surface. Such complexity imposes some difficulties for differentiating subtle surface luster properties of diverse textile fabrics. The advancement in the area of imaging technologies has enabled the micro-scale analysis of the surface textures and the fabric luster recently. Using a CCD camera, the surface luster images were taken at various incident illumination conditions. Microscale analysis, including the blob analysis, of the images could differentiate the subtle luster properties present in a group of cotton fabric samples comprising mercerized cotton fabric, non-mercerized cotton fabric, polished cotton fabric, and a 'standard' cotton fabric. The glossmeter measurement gave satisfactory but limited differentiation among the samples, whose luster differences are easily recognizable with visual observation, except for the mercerized cotton fabric sample and the non-mercerized cotton fabric. The microscale analysis of the fabric luster could, therefore, help understand the nature of diverse textile fabric luster.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.801-805
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• 2006

In this paper, we describe a system of controlling the pictorial puzzle program using information of hand shape. We extract hand region using skin color information and then principal component analysis uses centroidal profile information which comes blob of 2D appearance for hand shape recognition. This method suit hand shape recognition in real time because it extracts hand region accurately, has little computation quantity, and is less sensitive to lighting change using skin color information in complicated background. Finally, we controlled a pictorial puzzle with using recognized hand shape information. This method has good result when we make an experiment on application of pictorial puzzle. Besides, it can use so many HCI field.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.92-99
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• 2004

The formation degree of sustain (ITO pattern) decides quality of PDP (Plasma Display Panel). For this reason, it makes efforts in searching defects more than 30 un as 100%. Now, the existing inspection is dependent upon naked eye or microscope in off-line PDP manufacturing process. In this study developed prototype inspection system of PDP 170 glass is based on line-scan mechanism. Developed system creates information that detects and sorts kinds of defect automatically. Designed inspection technology adopts multi-vision method by slip-beam formation for the minimum of inspection time and detection algorithm is embodied in detection ability of developed system. Designed algorithm had to make good use of kernel matrix that draws up an approach to geometry. A characteristic of defects, as pin hole, substance, protrusion, are extracted from blob analysis method. Defects, as open, short, spots and et al, are distinguished by line type inspection algorithm. In experiment, we could have ensured ability of inspection that can be detected with reliability of up to 95% in about 60 seconds.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.716-725
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• 2007

In this paper we describe a motion tracking algorithm for 3D human animation using stereo vision system. This allows us to extract the motion data of the end effectors of human body by following the movement through segmentation process in HIS or RGB color model, and then blob analysis is used to detect robust shape. When two hands or two foots are crossed at any position and become disjointed, an adaptive algorithm is presented to recognize whether it is left or right one. And the real motion is the 3-D coordinate motion. A mono image data is a data of 2D coordinate. This data doesn't acquire distance from a camera. By stereo vision like human vision, we can acquire a data of 3D motion such as left, right motion from bottom and distance of objects from camera. This requests a depth value including x axis and y axis coordinate in mono image for transforming 3D coordinate. This depth value(z axis) is calculated by disparity of stereo vision by using only end-effectors of images. The position of the inner joints is calculated and 3D character can be visualized using inverse kinematics.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.18-23
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• 2006

The formation degree of sustain (ITO pattern) determines the quality of a PDP (Plasma Display Panel). Thus, in the present study, we attempt to detect 100% of the defects that are larger than $30{\mu}m$. Currently, the inspection method in the PDP manufacturing process is dependent upon the naked eye or a microscope in off-line mode. In this study, a prototype inspection system for PDP ITO patterned glass is developed. The developed system, which is based on a line-scan mechanism, obtains information on the defects and sorts the defects by type automatically. The developed inspection system adopts a multi-vision method using slit-beam formation for minimum inspection time and the detection algorithm is embodied in the detection ability. Characteristic defects such as pin holes, substances, and protrusions are extracted using the blob analysis method. Defects such as open, short, spots and others are distinguished by the line type inspection algorithm. It was experimentally verified that the developed inspection system can detect defects with reliability of up to 95% in about 60 seconds for the 42-inch PDP panel.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.191-195
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• 2003

The formation degree of sustain (ITO pattern) decides quality of PDP (plasma display panel). For this reason. it makes efforts in search defects more than 30 ${\mu}{\textrm}{m}$. Now, the existing inspection process is dependent upon naked eye or SEM equipment in off-line PDP manufacturing process. In this study developed prototype inspection system of PDP ITO glass. This system creates information that detects and sorts kind of defect automatically. Design ed inspection technology adopts line-scan method by slip-beam formation for the minimum of inspection time and image processing algorithm is embodied in detection ability of developed system. Designed algorithm had to make good use of kernel matrix which draws up an approach to geometry. A characteristic of area-shaped defects, as pin hole, substance, protrusion et al, are extracted from blob analysis method. Defects, as open, short, spots, et al, are distinguished by line type inspection algorithm. In experiment results, we could have ensured ability of inspection that can be detected with reliability of up to 95% in about 60 seconds