• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.494-499
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• 2007

실제 영상과 가상의 오브젝트 또는 가상의 환경에 오브젝트를 합성하는 경우 등 사실적인 합성을 결과를 얻기 위해서는 실제 환경과 같은 배경 영상의 정확한 광원 정보가 필요하다. 본 논문에서는 실내 환경을 배경으로 영상을 합성 하는 과정에 필요한 광원정보를 카메라와 Light Probe를 이용하여 촬영된 단일 영상으로부터 추정하는 기법을 제안한다. 실내에 존재하는 광원들은 정확한 위치정보를 알 수 없는 실외환경에서와 달리 제한된 공간의 원점으로부터 3차원 공간에 위치한 좌표로 나타낼 수 있다. 광원을 추정하기 위해 먼저 실내 공간에 반사도가 높은 Light Probe를 위치하고 디지털 카메라의 적정 노출을 이용하여 광원 추정에 사용할 영상을 획득한다. 광원으로 존재하는 오브젝트의 경우 짧은 노출시간에도 카메라의 영상에 획득된다. 그렇기 때문에 단일 영상에서 광원의 영역을 추정하기 위해 영상처리를 통해 노출 시간을 짧게 하여 촬영한 영상과 비슷하게 밝은 영역만 표현되도록 처리를 한다. 전 처리된 영상으로부터 밝은 영역과 어두운 영역으로 구분을 하고 밝은 영역으로부터 광원의 정보를 추정한다. 추정된 광원들은 실제 렌더링에 곧바로 적용이 가능하며, 이를 통해 배경에 적합한 렌더링 결과를 얻을 수 있다.

• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.368-375
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• 2010

Unlike document images, license plate images are mostly captured under uneven lighting conditions. In particular, a shadowed region has sharp intensity variation and sometimes that region has very high intensity by reflected light. This paper presents a new technique for thresholding license plate images. This approach consists of three parts. In the first part, it performs a rough thresholding and classifies the type of license plate to adjust some parameters optimally. Next, it identifies a shadow type and binarizes license plate images by adjusting the window size and location according to the shadow type. And finally, post-processing based on the cluster analysis is performed. Experimental results show that the proposed method outperformed five well-known methods.

• Journal of Biosystems Engineering
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• v.19 no.4
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• pp.380-396
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• 1994

A personal computer based color machine vision system with video camera and fluorescent lighting system was used to generate images of stationary tobacco leaves. Image processing algorithms were developed to extract both the geometric and the color features of tobacco leaves. Geometric features include area, perimeter, centroid, roundness and complex ratio. Color calibration scheme was developed to convert measured pixel values to the standard color unit using both statistics and artificial neural network algorithm. Improved back propagation algorithm showed less sum of square errors than multiple linear regression. Color features provide not only quality evaluation quantities but the accurate color measurement. Those quality features would be useful in grading tobacco automatically. This system would also be useful in measuring visual features of other agricultural products.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.69-72
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• 2002

Human face detection has many applications such as face recognition, face or facial feature tracking, pose estimation, and expression recognition. We present a new method for automatically segmentation and face detection in color images. Skin color alone is usually not sufficient to detect face, so we combine the color segmentation and shape analysis. The algorithm consists of two stages. First, skin color regions are segmented based on the chrominance component of the input image. Then regions with elliptical shape are selected as face hypotheses. They are certificated to searching for the facial features in their interior, Experimental results demonstrate successful detection over a wide variety of facial variations in scale, rotation, pose, lighting conditions.

• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.79-85
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• 2010

In this paper, we propose a web inspection system (WIS) for real-time detection of paper defects which can cause critical fractures during papermaking process. Our system incorporates high speed line-scan camera, lighting system, and detection algorithm to provide robust and precise detection of paper defects in real-time. Since edge defects are very crucial to the paper fractures, our system focuses on the edge region of the paper instead of inspecting the whole paper area. In our algorithm, image projection and sub-pixel operation are utilized to detect the edge defects precisely and connected component labeling and shape analysis techniques are adopted to extract various kinds of the region defects. Experimental results revealed that our web inspection system is very efficient for detecting paper defects during papermaking processes.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.818-820
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• 2022

The keyword 'healing' is essential to the competitive society and culture of Koreans. In addition, as the time at home increases due to COVID-19, the demand for indoor healing services has increased. Therefore, this thesis analyzes the user's facial expression so that people can receive various 'customized' healing services indoors, and based on this, provides lighting, ASMR, video recommendation service, and facial expression recording service.The user's expression was analyzed by applying the ensemble algorithm to the expression prediction results of various CNN models after extracting only the face through object detection from the image taken by the user.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.11
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• pp.755-762
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• 2014

In recent year, along with the rapid development of LED technology, many applications using LEDs with Visible Light Communication(VLC) have been researched. Since it is easy to provide LOS communication environment along with cheap deployment cost, the indoor positioning system based on VLC has been actively studied. In this paper, we propose an accurate indoor positioning algorithm using a stereo image sensor and white-light LEDs with the visible light communication. Indoor white-light LEDs are located at the ceiling of a room and broadcast their position information by VLC technology. Mobile receiver with stereo image sensor receives LED position information by VLC and estimates its position and angle information. Simulation results are given to show the efficiency of proposed indoor positioning algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1690-1710
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• 2014

In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.332-336
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• 2010

There are so many successful applications to image processing systems in industries. In this study we propose a position detection system for used oil filter by using a line laser. We have been done on the development of line laser as interaction devices. A camera captures images of a display surface of a used oil filter and then a laser beam location is extracted from the captured image. This image is processed and used as a cursor position. We also discuss an algorithm that can distinguish the front part and rear part. In particular we present a robust and efficient linear detection algorithm that allows us to use our system under a variety lighting conditions, and allows us to reduce the amount of image parsing required to find a laser position by an order of magnitude.

• 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.