• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1851_1852
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• 2009

본 논문은 차량 영역에 나타나는 수평, 수직 에지 특성만을 이용하여 빠르고 효율적으로 차량을 검출하는 방법을 제안한다. 차량을 포함하는 입력영상의 긴 수직 에지 성분을 찾아 차량의 후보 영역을 결정한다. 영상의 에지 성분의 누적 대신 연속적으로 나타나는 긴 수직 에지 성분을 찾음으로써 차량의 후보 영역의 검출과 동시에 중요한 정보를 담고 있는 도로와 접하는 차량의 하단부를 함께 검출한다. 후보 영역 내에서 차량과 비 차량을 구분하는 검증 단계에서는 차량의 후면의 대칭성(Symmetry)을 이용하여 후보 영역 내에서 차량이 있을 가능성이 있는 바닥 점 위에서 좌측과 우측의 유사도(Matching rate)를 이용하여 차량과 비 차량을 판별한다. 기존의 템플릿 기반 방법이나 외관 기반 방법이 아닌 에지 성분만을 이용하여 후보 영역을 결정하고 검증하기 때문에 다른 검출 기법들에 비해 비교적 검출 시간이 짧고 실시간 차량 검출에 적합하다.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.652-657
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• 1986

본 연구는 시야나 머리운동을 구속하지 않고 수평 및 수직 머리운동을 측정하여 처리하는 방법에 관한 것이다. 이를 위해 Helmholtz 코일을 적절히 구성하여 균일 자계를 발생시키고 탐지 코일을 이용하여 머리운동의 동적 특성을 검출하고, 검출된 신호는 신호처리 장치를 구성하여 처리하는 방법을 개발하고 다른 연구결과와 비료 고찰하였다.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2404-2406
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• 2005

본 연구에서는 전기촉매제를 사용하여 증가된 감도를 가지는 검출 시스템을 제작하였다. 전극과 검출물질 사이의 산화환원반응을 촉진시키기 위한 물질로 Prussian blue (PB)를 indium tin oxide (ITO) 전극에 전착하였다. 본 실험에서는 분석물질의 이동 및 분리를 위하여 모세관 전기영동방법을 사용하였으며 측정방법은 전류량법을 사용하였다. 전착된 PB 박막의 특성은 원자 현미경으로 분석하여 0.1V, 3min의 전착조건으로 최적화하였다. 전기 촉매제로써의 PB의 특성을 확인하기 위하여 ITO 전극만을 사용한 전기화학적 검출기와 비교하였으며 본 연구에서 제안된 검출기의 감도가 20배정도 더 좋다는 것을 확인하였다.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.117-124
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• 2013

In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.218-223
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• 2013

The performances of previous edge detection methods such as Sobel, Prewitt, and LoG(Laplacian of Gaussian) are insufficient for images degraded in AWGN(additive white Gaussian noise). Therefore, in this paper, we proposed an edge detection algorithm using a modified coefficient masks with gradient masks and distance weight mask. In order to confirm and verify the performance of the proposed algorithm, we simulated and compared proposed algorithm to conventional methods on various standard images added AWGN with a standard deviation ${\sigma}$=15, 30 and proposed algorithm shows superior edge detection characteristics in processed images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.96-101
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• 2011

Vanishing point can be defined as a point generated by converged perspective lines, which are parallel in the real world. In this paper, we propose a real-time vanishing point detection algorithm using this fundamental feature of vanishing point. The existing methods 1) require high computational cost or 2) are restricted to specific image contents. The proposed method detects the vanishing point in images based on the block-wise HOG (Histogram of Oriented Gradient) descriptor. First, we compute the HOG descriptor in a block-wise manner, then estimate the location of the vanishing point using the proposed dynamic programing. Experiments are performed on diverse images to confirm the efficiency of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1518-1523
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• 2012

Due to development of visual media in various industrial sectors, the importance of image processing is increasing. Among the various image processing areas, edge detection is utilized widely for various fields such as object recognition, object segmentation, the medical and other industries. Edge includes the critical factors of images like size, direction and location. Then conventional methods such as Sobel, Prewitt, Roberts and Laplacian are proposed to detect edge. However, edge detection property of these methods is declined when they are applied to the image which corrupted by AWGN(Additive White Gaussian Noise). Therefore, an algorithm using modified weighted filter is proposed in this paper and our method has excellent property on edge detection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.328-330
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• 2015

Edge is a characteristic information that can easily obtain the size, direction and location of objects included in the image, and the edge detection is utilized as a preprocess processing in various image processing application sectors such as object detection and object recognition, etc. For the conventional edge detection methods, there are Sobel, Prewitt and Roberts. These existing edge detection methods are easy to implement but the edge detection characteristics are somewhat insufficient as fixed weighted mask is applied. Therefore, in order to compensate the problems of existing edge detection methods, in this paper, an edge detection algorithm was proposed after applying the weighted value according to the standard deviation and means within the local mask.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.238-242
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• 2004

운송 컨테이너의 식별자를 추출하는 것은 컨테이너 식별자들의 크기나 위치가 정형화되어 있지 않고 외부의 잡음으로 인하여 식별자의 형태가 훼손되어 있기 때문에 어렵다. 본 논문에서는 이러한 특성을 고려하여 컨테이너 영상에 대해 Canny 마스크를 이용하여 에지를 검출하고, 검출된 에지 정보에서 영상획득 시 외부 광원에 의해 수직으로 길게 발생하는 잡음들을 퍼지추론 방법을 적용하여 제거한 후에 수직 블록과 수평 블록을 검출하여 컨테이너의 식별자 영역을 추출한다. 추출된 컨테이너의 식별자 영역에서 히스토그램 방법과 윤곽선 추적 알고리즘을 각각 이용하여 개별 식별자를 추출한다. 실제 컨테이너 영상을 대상으로 실험 결과, 제안된 컨테이너 식별자 추출 방법이 다양한 컨테이너 영상에 대해 효율적인 것을 확인하였다.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.26-31
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• 2014

In this paper, we present performance analysis of video smoke detection based on BPN-Network that is using multi-smoke feature, and Neural Network. Conventional smoke detection method consist of simple or mixed functions using color, temporal, spatial characteristics. However, most of all, they don't consider the early fire conditions. In this paper, we analysis the smoke color and motion characteristics, and revised distinguish the candidate smoke region. Smoke diffusion, transparency and shape features are used for detection stage. Then it apply the BPN-Network (Back-Propagation Neural Network). The simulation results showed 91.31% accuracy and 2.62% of false detection rate.