• Journal of Mechanical Science and Technology
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• v.15 no.12
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• pp.1808-1815
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• 2001

The characteristics of a pulsed plasma jet originating from an electrothermal capillary discharge have been investigate using laser-induced fluorescence (LIF) measurement. Previous emission measurements of a 3.1 kJ plasma jet show trial upstream of the Mach disk the temperature and electron number density are about 14,000 K and and 10$\^$17/ cm$\^$-3/, while downstream of the Mach dick tole values are about 25,000 K and 10$\^$18/ cm$\^$-3/, respectively. However, these values are barred on line-of-sight integrated measurements that may be misleading. Hence, LIF is being used to provide both spatially and temporally resolved measurements. Our recent work has been directed at using planar laser-induced fluorescence (PLIF) imaging of atomic copper in the plasma jet flow field. Copper is a good candidate for PLIF studies because it is present throughout the plasma and has electronic transitions that provide an excellent pump-detect strategy. Our PLIF results to date show that emission measurements may give a misleading picture of the flow field, as there appeals to be a large amount of relatively low temperature copper outside the barrel shock. which may lead to errors in temperature inferred from emission spectroscopy. In this paper, the copper LIF image is presented and at the moment, relative density of atomic copper, which is distributed in the upstream of the pulsed plasma jet, is discussed qualitatively.

• Journal of the Korea Society of Computer and Information
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• v.17 no.5
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• pp.29-32
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• 2012

In this paper, we propose a novel method to extract muscle area from lumbar ultrasonographic image. The muscle area resided in lumbar area can be defined as the area between thoracic vertebra and subcutaneous fat area. A modified 4-directional contour tracing algorithm is designed to detect the boundaries and candidate areas are extracted and verified by the morphological characteristics of lumbar area. The experiment using 392 lumbar images verifies that the proposed method is sufficiently effective by showing over 94% accuracy in extraction.

• Journal of Advanced Navigation Technology
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• v.18 no.4
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• pp.387-392
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• 2014

Recently, various research for intelligent video surveillance system have been proposed, but the existing monitoring systems are inefficient because all of situational awareness is judged by the human. In this paper, shadow removal based moving object tracking method is proposed using the chromaticity and entropy image. The background subtraction model, effective in the context awareness environment, has been applied for moving object detection. After detecting the region of moving object, the shadow candidate region has been estimated and removed by RGB based chromaticity and minimum cross entropy images. For the validity of the proposed method, the highway video is used to experiment. Some experiments are conducted so as to verify the proposed method, and as a result, shadow removal and moving object tracking are well performed.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.27-34
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• 2004

This thesis proposes a face detection algorithm using the color and edge informations in color image. The proposed algorithm segments skin color by Cb and Cr in YCbCr coordinates. Then face candidate regions are made after morphological filtering and labeling. For the regions, the Sobel vortical operation and horizontal projection are performed in the Y luminance components. The peak value indicates the eye location. Similarly, the chin location is detected by the Sobel horizontal operation and horizontal projection. The computer simulation shows that the proposed method gains similar detection rates of previous method and prevent facial region from including neck by detection of chin.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.236-238
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• 2003

Human face detection is often the first step in applications such as video surveillance, human computer interface, fare recognition, and image database management. We have constructed a simple and fast system to detect frontal human faces in complex environment and different illumination. This paper presents a fast segmentation method to combine neighboring pixels with similar hue. The algorithm constructs eye, mouth, and boundary maps for verifying each fare candidate. We test the system on images in complex environment and with confusing objects. The experiment shows a robust detection result with few false detected fates.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.813-816
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• 2005

Ear detection is an important part of an non-invasive ear recognition system. In this paper we propose human ear detection from side face images. The proposed method is made by imitating the human recognition process using feature information and color information. First, we search face candidate area in an input image by using 'skin-color model' and try to find an ear area based on edge information. Then, to verify whether it is the ear area or not, we use the SVM (Support Vector Machine) based on a statistical theory. The method shows high detection ratio in indoors environment with stable illumination.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.471-477
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1cm, ${\pm}$24.7cm, ${\pm}$35.9cm, respectively.

• Molecules and Cells
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• v.23 no.2
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• pp.170-174
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• 2007

High-throughput subcellular imaging is a powerful tool for investigating the function of genes. In order to identify novel regulators of apoptosis we transiently transfected HeLa cells with 938 hypothetical genes of unknown function, and captured their nuclear images with an automated fluorescence microscope. We selected genes that induced greater than 3-fold increase in the percentage of apoptotic nuclei compared with vector-transfected cells. The full-length genes C10orf61, MGC 26717, and FLJ13855 were identified as candidate proapoptotic genes, and their apoptotic effects were confirmed by DNA fragmentation ELISAs and Western blotting for caspase-7 and PARP. We conclude that a subcellular image-based apoptotic screen is useful for identifying genes with proapoptotic activity.

• The Journal of Korea Robotics Society
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• v.10 no.4
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• pp.223-229
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• 2015

This paper proposes a novel method for detection of hand raising poses from images acquired from a single camera attached to a mobile robot that navigates unknown dynamic environments. Due to unconstrained illumination, a high level of variance in human appearances and unpredictable backgrounds, detecting hand raising gestures from an image acquired from a camera attached to a mobile robot is very challenging. The proposed method first detects faces to determine the region of interest (ROI), and in this ROI, we detect hands by using a HOG-based hand detector. By using the color distribution of the face region, we evaluate each candidate in the detected hand region. To deal with cases of failure in face detection, we also use a HOG-based hand raising pose detector. Unlike other hand raising pose detector systems, we evaluate our algorithm with images acquired from the camera and images obtained from the Internet that contain unknown backgrounds and unconstrained illumination. The level of variance in hand raising poses in these images is very high. Our experiment results show that the proposed method robustly detects hand raising poses in complex backgrounds and unknown lighting conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5563-5582
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• 2016

Parametric min-cuts is an object proposal algorithm, which can be used for accurate image segmentation. In parametric min-cuts, foreground seeds generation plays an important role since the number and quality of foreground seeds have great effect on its efficiency and accuracy. To improve the performance of parametric min-cuts, this paper proposes a new framework for foreground seeds generation. First, to increase the odds of finding objects, saliency detection at multiple scales is used to generate a large set of diverse candidate seeds. Second, to further select good-quality seeds, a two-stage cascaded ranking classifier is used to filter and rank the candidates based on their appearance features. Experimental results show that parametric min-cuts using our seeding strategy can obtain a relative small pool of proposals with high accuracy.