• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.4 s.27
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• pp.261-266
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• 2006

In this study, a scaled model chamber was built to investigate ventilation characteristics of the hood room in LNG carrier. Experimental study was performed in model by visualization equipment with laser apparatus. Four different kinds of measuring area were selected as experimental condition Instant simultaneous velocity vectors at whole field were measured by 2-D PIV system and its software adopting two-frame grey-level cross correlation algorithm. The flow pattern reveals the large scale counter-clockwise forced-vortex rotation at center area.

• Journal of IKEEE
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• v.24 no.2
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• pp.502-506
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• 2020

With the development of autonomous driving technology, the importance of object recognition technology is increasing. Haze removal is required because the hazy weather reduces visibility and detectability in object recognition. However, the image from which the haze has been removed cannot properly reflect the unique color, and a detection error occurs. In this paper, we use CIE1931 color coordinate system to extend or reduce the color area to provide algorithms and hardware that reflect the colors of the real world. In addition, we will implement hardware capable of real-time processing in a 4K environment as the image media develops. This hardware was written in Verilog and implemented on the SoC verification board.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.10a
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• pp.93-98
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• 2009

Comprehension of physical properties distribution of underground cavity must be made primarily to show the clear image of the state of the cavity. A physical scale model experiment is executed assuming that underground cavity in filled with air or water of different ratio. The state of cavity wall is considered wet. Cavity model is made of agar. As a experimental result, even if the cavity wall is wet, high air and water ratio cavity shows high anomaly.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.11-22
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• 2006

Recently face detection has actively been researched due to its wide range of applications, such as personal identification and security systems. In this paper, a new face detection method based on the distribution map is proposed. Face-like regions are first extracted by applying the skin color map with the frequency to a color image and then, possible eye regions are determined by using the pupil color distribution map within the face-like regions. This enables the reduction of space for finding facial features. Eye candidates are detected by means of a template matching method using weighted window, which utilizes the correlation values of the luminance component and chrominance components as feature vectors. Finally, a cost function for mouth detection and location information between the facial features are applied to each pair of the eye candidates for face detection. Experimental results show that the proposed method can achieve a high performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.6
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• pp.929-938
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• 2000

A summary of the development and verifications of a computer code being developed at Pohang University of Science and Technology (POSTECH) for calculating the radar cross section(RCS) of complex targets is presented. The complex targets are modeled in terms of patches and wedges. This code utilizes physical optics, physical theory of diffraction and shooting and bouncing rays method to calculate the RCS of complex targets. For the verification of the RCS prediction code, a simple-shaped scale-model was manufactured and the RCS was measured at the POSTECH compact range. The obtained RCS was processed to give frequency-domain RCS patterns and ISAR images. The predicted RCS shows good agreement with measured one. The RCS prediction methods presented here are applicable to stealth design and target recognition.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.31-36
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• 2003

This paper proposes an acceleration method of PCA(Principal Component Analysis) based feature detection. The feature detection method makes decision whether the target feature is included in a given image, and if included, calculates the position and extent of the target feature. The position and scale of the target feature or face is not known previously, all the possible locations should be tested for various scales to detect the target. This is a search Problem in huge search space. This Paper proposes a fast face and feature detection method by reducing the search space using the multi-stage prediction map and contour Prediction map. A Proposed method compared to the existing whole search way, and it was able to reduce a computational complexity below 10％ by experiment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.175-180
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• 2018

In this paper, a feature extraction and object recognition algorithm using only morphological operations is proposed. The morphological operations used in feature extraction are erosion and dilation, opening and closing combining erosion and dilation, and morphological edge and skeleton detection operation. In the process of recognizing an object based on features, a pooling operation is applied to reduce the dimension. Among various structuring elements, $3{\times}3$ rhombus, $3{\times}3$ square, and $5{\times}5$ circle are arbitrarily selected in morphological operation process. It has confirmed that the proposed algorithm can be applied in object recognition fields through experiments using Internet images.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.77-82
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• 2012

This paper presents a hardware-implemented face regions stabilization algorithm that stabilizes facial regions using the locations and sizes of human faces found by a face detection system. Face detection algorithms extract facial features or patterns determining the presence of a face from a video source and detect faces via a classifier trained on example faces. But face detection results has big variations in the detected locations and sizes of faces by slight shaking. To address this problem, the high frequency reduce filter that reduces variations in the detected face regions by taking into account the face range information between the current and previous video frames are implemented in addition to center distance comparison and zooming operations.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.873-876
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• 2004

사람의 동작을 인식하는 것에 대한 연구는 게임, 유비쿼터스 컴퓨팅 등의 발전에 따라 그 중요성이 증가하고 있다. 그러나, 대부분의 기존 연구에서는 극히 소수의 동작만을 정의하거나 특정 부위의 동작만을 다루므로 실제 응용에 적용하기에는 적합하지 않다. 본 논문에서는 특정 도메인의 사용 없이, 카메라 영상 입력으로 취득된 동작 패턴 정보만을 이용하여 40종 전신 연속 동작을 구분하는 동작인식 방법을 연구하였다. 인식에 사용된 입력 데이터는 동작자 관절들의 위치 및 회전 값들이며, 다수의 동작들을 인식하기 위해서는 기존의 인식 알고리즘들인 특징기반 인식, HMM, 신경망(Neural Network)등을 사용하여 복합적인 인식 엔진을 구성하여야 했다. 입력 데이터별로 적합한 인식 모듈을 거치게 하기 위해서는, 동작에 의한 입력 데이터에서 동작자 움직임의 주요 신체 부위를 추출함으로써 입력 데이터가 해당 그룹의 인식 모듈로 자동적으로 분류되게 하는 방법을 사용한다. 이는 다층의 인식 레이어 중 복잡도가 증가하는 하위 레이어일수록 자동 분류에 의해 걸러진 데이터만을 취급하게 되므로 효과적이다. 전체 실험 결과 단계별로 약 79~97%의 인식률을 보였다. 이는 향후 특정 컨텍스트 정보와 결합할 때 매우 높은 인식률을 기대할 수 있게 하는 수치이다.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1009-1024
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• 2018

With the increased use of LiDAR (Light Detection and Ranging) that can obtain over millions of point dataset, methodologies for efficient search and dimensionality reduction for the point cloud became a crucial technique. The existing octree-based "parametric algorithm" has proved its efficiency and contributed as a part of PCL (Point Cloud Library). However, the implementation of the algorithm on GPU (Graphics Processing Unit) is considered very difficult because of structural constraints of the octree implemented in PCL. In this paper, we present a method for the parametric algorithm on GPU environment and implement a projection of the queried points on four directions with an improved noise reduction.