• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.237-240
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• 2007

이 논문에서는 수정된 Sequential Algorithmic Schema를 이용해서 여러 장소를 이동하면서 찍은 디지털 이미지를 효율적으로 분류할 수 있는 방법을 제안한다. 제안하는 방법은 이웃 패턴들과 특징 정보의 연속성, 유사성을 가지며 들어오는 입력 패턴에 대해 기존의 모든 군집과 유사도를 비교하는 방법이 아니라 이전 군집의 정보와 유사도를 비교하여 군집에 포함시키거나 동적으로 군집을 생성하는 효율적인 군집화 방법이다. 제안한 방법은 실험을 통해서 기존의 군집화 기법에 성능 및 속도의 효율성을 증명하였다.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1069-1072
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• 2009

Field sequential display has some advantages but color breakup (CBU) is the significant problem. Many researches had introduced several methods to reduce CBU phenomenon, however there are no reliable methods to measure the degree of CBU. In this report, a novel CBU measurement technique which was based on the image processing method and subjective analysis results had proposed to evaluate the degree of CBU. Color Breakup Index (CBI) was presented to be a useful index to recognize the CBU phenomenon in the different field sequential technique displays.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.331-341
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• 2002

In order to extract 3-dimensional information from 2-D image, stereo images are prerequisite. Moreover, for the measurement of moving objects, the synchronized sequential stereo images have to be captured and image matching should be implemented for determining the location of moving objects. In this research, a simple method computing 3-dimensional coordinates from sequential images of moving objects was implemented. The sequential stereo images were captured by a video camera with a beam splitter. Once video images were digitalized by frame grabber, the interest points were extracted and matched in each stereo image, and the coordinates of center of them are calculated using weighted average method. Then, 3-dimensional coordinates of moving objects were computed by DLT algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.69-79
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• 1994

DCT image coding has been well known for its compression efficiency. Its nature makes it also suitable for efficient progressive transmission and reconstruction since low frequency transform coefficients contain most of the energy of image signals. In this paper, we propose a progressive transmission technique of DCT image by non-sequential bit ordering using Lloyd-Max quantizer. And then, we will show that the Lloyd-Max quantizer can be embedded quantization. In simulation results, the proposed method show better subjective picture and MSE of the reconstructed image than the conventional zig-zag scanning transmission of transform coefficients.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1544-1548
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• 2011

A process of choosing a subset of original features, so called feature selection, is considered as a crucial preprocessing step to image processing applications. There are already large pools of techniques developed for machine learning and data mining fields. In this paper, basically two methods, non-feature selection and feature selection, are investigated to compare their predictive effectiveness of classification. Color co-occurrence feature is used for defining image features. Standard Sequential Forward Selection algorithm are used for feature selection to identify relevant features and redundancy among relevant features. Four color spaces, RGB, YCbCr, HSV, and Gaussian space are considered for computing color co-occurrence features. Gray-level image feature is also considered for the performance comparison reasons. The experimental results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• Journal of the Optical Society of Korea
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• v.18 no.6
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• pp.777-782
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• 2014

This paper proposes an RGB to RGBY color conversion algorithm for liquid crystal display (LCD) using RGW pixel structure with two-field (yellow and blue) sequential driving method. The proposed algorithm preserves the hue and saturation of the original color by maintaining the RGB ratio, and it increases the luminance. The performance of the proposed RGBY conversion algorithm is verified using the MATLAB simulation with 24 images of Kodak lossless true color image suite. The simulation results of average color difference CIEDE2000 (${\delta}E^*_{00}$) and scaling factor are 0.99 and 1.89, respectively. These results indicate that the average brightness is increased 1.89 times compared to LCD using conventional RGB pixel structure, without increasing the power consumption and degrading the image quality.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.124-127
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• 1997

In this paper, we propose the new face detection and tracking angorithm in sequential images which have complex background. In order to apply face deteciton algorithm efficently, we convert the conventional RGB coordiantes into CIE coordonates and make the input images insensitive to luminace. And human face shapes and colors are learned using ueural network's backpropagation. For variable face size, we make mosaic size of input images vary and get the face location with various size through neural network. Besides, in sequential images, we suggest face motion tracking algorithm through image substraction processing and thresholding. At this time, for accurate face tracking, we use the face location of previous. image. Finally, we verify the real-time applicability of the proposed algorithm by the simple simulation.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.2 s.8
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• pp.47-54
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• 1996

It needs more than two images which are obtained in real time to decide 3D positioning of dynamic object. Though we use digital camera which is became wide utilization, but it can't obtain sequential image. So, in this study, we constructed momentary image acquisition system using video camera. Also, we took a photograph of LCD timer and dynamic object together for real time stereo image, and we obtained independent digital image from sequential image using video editor. As a result of the study, we could obtain the independent image as true color digital image of $788{\times}550$pixels with 1/100sec accuracy in the same time. And it was good when we tested object target. For comparing 3D positioning accuracy, we could obtained negative with metric camera using B-shutter.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.73-83
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• 2015

This paper proposes a TFT-LCD defect blob detection algorithm using the sequential defect detection method. First, for every pixel, a defect possibility is determined by the intensity difference and the defect candidates are detected according to the sequential defect detection method. For detected candidate pixels, the defect probability that indicates a potential included in the defect according to the each step. By applying the morphological operation, blobs are comprised of the detected candidates and the defect blobs are detected using the defect possibility of blobs. The validity of the proposed method was demonstrated a simulated image and also then it was tested a real TFT-LCD image. By the experimental results, the proposed method is very effective in TFT-LCD detect detection.