• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.21-29
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• 2000

In this paper, we propose a way to detect a moving object efficiently and to track it using the active blocks. Instead of all Pixels in 8*8 Pixel value, any special pixel is extracted and we detect a moving object by comparison and by analysis the difference image information from darkness value of the same area. In the acquisition of image data by software processing, we reduce the number of data which obtain by convert high resolution image to low resolution image, and we can track a moving object in real time. So it can track a moving object in simple system without all the pixel value of the image data or additional VxD(Virtual x Driver). This system can be useful to track of a moving object in fixed block on PC(Personal Computer) and low custom.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.137-146
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• 1998

Recently many devices print electronic images in a variety of ways. The reproduced color, however, is different from the original color because of the difference of hardware characteristics. To maintain device independent color, gamut mapping method is proposed. The proposed color gamut mapping uses nonlinear intensity mapping and clipping for saturation mapping on HSI color space. In the dithering operation, expanded nonlinear ordered dithering and modified error diffusion are proposed. The proposed ordered dithering uses expanded nonlinear quantization which considers overlapping phenomena of neighbored printing dots. In the modified error diffusion, quantization errors to be diffused are adjusted to improve both image blur and color change produced in the error diffusion. So, the printed image is similar to the image of monitor. Our results indicate that proposed algorithm can produce high quality image in the low bit color devices.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.44-50
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• 2007

In this paper, we proposed the algorithm for the extraction of the corresponding points from images. The proposed algorithm EMSAC is based on RANSAC and EM algorithms. In the RANSAC procedure, the N corresponding points are randomly selected from the observed total corresponding points to estimate the homography matrix, H. This procedure continues on its repetition until the optimum H are estimated within number of repetition maximum. Therefore, it takes much time and does not converge sometimes. To overcome the drawbacks, the EM algorithm was used for the selection of N corresponding points. The EM algorithm extracts the corresponding points with the highest probability density to estimate the optimum H. By the experiments, it is demonstrated that the proposed method has exact and fast performance on extraction of corresponding points by combining RANSAC with EM.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.51-59
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• 2007

In this paper, we propose an efficient hardware architecture for H.264/AVC CAVLC (Context-based Adaptive Variable Length Coding) decoding which used for baseline profile and extended profile. Previous CAVLC architectures are consisted of five step block and each block gets effective bits from Controller block and Accumulator. If large number of non-zero coefficients exist, process for getting effective bits has to iterates many times. In order to reduce this unnecessary process, we propose two techniques, which combine five steps into four steps and reduce process to get efficiency bit by skipping addition step. By adopting these two techniques, the required processing time was reduced about 26% compared with previous architectures. It was designed in a hardware description language and total logic gate count was 16.83k using 0.18um standard cell library.

• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.21-30
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• 2005

In general, the robust estimation method is well known for a good statistical estimator that is insensitive to small departures from the idealized assumptions for which the estimation is optimized. While there are many existing robust estimation techniques that have been proposed in the literature, two main techniques used in computer vision are M-estimators and least-median of squares (LMS). Among these. we utilized the M-estimators since they are known to provide an optimal estimation of affine motion parameters. The M-estimators have higher statistical efficiency but tolerate much lower percentages of outliers unless properly initialized. To resolve these problems, we proposed an adaptive M-estimators algorithm that effectively separates outliers from non-outliers and estimate affine model parameters, using a continuous sigmoid weight function. The experimental results show the superiority of our method.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.59-65
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• 2019

Hospital Information System includes a wide range of information in the medical profession, from the overall administrative work of the hospital to the medical work of doctors. In this paper, we proposed a Vision-based Authentication and Registration of Facial Identity in Hospital Information System using OpenCV. By using the proposed security module program a Vision-based Authentication and Registration of Facial Identity, the hospital information system was designed to enhance the security through registration of the face in the hospital personnel and to process the receipt, treatment, and prescription process without any secondary leakage of personal information. The implemented security module program eliminates the need for printing, exposing and recognizing the existing sticker paper tags and wristband type personal information that can be checked by the nurse in the hospital information system. In contrast to the original, the security module program is inputted with ID and password instead to improve privacy and recognition rate.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.117-124
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• 2014

Cluttered background is a major obstacle in developing salient object detection and tracking system for mobile device captured natural scene video frames. In this paper we propose a context aware feature vector selection model to provide an efficient noise filtering by machine learning based classifiers. Since the context awareness for feature selection is achieved by searching nearest neighborhoods, known as NP hard problem, we apply a fast approximation method with complexity analysis in details. Separability enhancement in feature vector space by adding the context aware feature subsets is studied rigorously using principal component analysis (PCA). Overall performance enhancement is quantified by the statistical measures in terms of the various machine learning models including MLP, SVM, Naïve Bayesian, CART. Summary of computational costs and performance enhancement is also presented.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.7
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• pp.47-52
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• 2009

H.264 video coding standard is widely used due to the high compression rate and quality. The motion compensation is the most time-consuming and complex unit in the H.264 decoder. The performance of the motion compensation is determined by the calculation of pixel interpolation and management of the reference pixels. The reference pixels read from external memory using efficient memory management for data reuse is necessary along with the high performance interpolators. We propose the architecture of a motion compensation unit for H.264 decoders. It is composed of 2-dimensional circular register files, a motion vector predictor and high performance interpolators with low complexity. The 2-dimensional circular register files reuse reference pixel data as much as possible, and feed reference pixel data to interpolators without any latency and complex logic circuits. We design a motion compensation unit and a intra-prediction unit and integrate them into a prediction unit and verify the operation and the performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.194-203
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• 2008

Though conventional video surveillance systems such as CCTV depended on operators, recently developed intelligent surveillance systems no longer needed operators. However, these new intelligent surveillance systems have their own problems such as Occlusion, changing scale of target object, and affine. This paper handled information damage caused by changing the scale of the target object among other objects. Due to the change of the scale, the inaccurate information of target can be obtained when we update the background information. To handle this problem, we introduce a solution for information damage caused by problem of changing scale of target object located among other objects. Specifically, we suggest multi-stage sampling particle filter based advanced MSER for object tracking system. Through this method, the problem caused by changing scale of target can be avoided.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.367-372
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• 2015

In this study, locality of scleroderma was detected. Diagnostic method is difficult for scleroderma (skin curing; Scleroderma), and it is done by comparing the images of the normal subjects to the scleroderma patients, after performing monochrome processing. The saturation, brightness, and contrast are adjusted, and they were converted by using the process of Well Filter. As a result, the images were able to be used to clearly distinguish the symptoms of scleroderma. In addition, in a video of a healthy person, the line of sight of the observation given the image of scleroderma patients above sea level of height as $0^{\circ}$ is to implement the closing process to the rear Well Filter even only in so that the horizontal plane, and out at intervals of graph the amplitude difference of the video have I asked. The diagnostic criteria were determined for the healthy subjects and the scleroderma patients.