• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.173-175
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• 2019

Animated images formats such as WebP are highly portable graphics formats that are being used everywhere on the Internet. Despite their small sizes and duration, WebP image previews the video without watching the entire content with minimum bandwidth. This paper proposed a novel method to generate personalized WebP images in the client side using its computation resources. The proposed system automatically extracts the WebP image from climax point using music analysis. Based on user interest, the system predicts the genre using Convolutional Neural Network (CNN). The proposed method can easily integrate with streaming platforms such as YouTube, Netflix, Hulu, and others.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.990-1002
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• 2016

In this paper, we propose a new compression method for the edge image by analyzing the characteristics and the distribution of pixel values of the edge image. The pixel values of the edge image have the Gaussian distribution around '0', and most of the pixel values are `0`. By these analyses we suggest the Zero-Based codec that expresses all values in a CU by a single bit flag. Also, in order to reduce the computational complexity of the proposed codec, the block partition and the intra-prediction techniques are proposed by using edge information like the number of each edge direction, the distribution and the amplitude of a major edge direction in the CU. Experimental results show that the proposed codec leads to a slighter distortion in Y domain than that of HEVC, but has far faster processing speed up to 53 times while it maintains the similar image quality compared to HEVC.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.19-28
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• 2017

In this paper, we propose a method to reduce the difference in image characteristics when multiple camera images are captured for virtual space production. Sixty-four images were used by cross-mounting eight bodies and lenses, respectively. Image analysis compares and analyzes the standard deviation of the histogram and pixel distribution values. As a result of the analysis, it shows different image characteristics depending on the lens or image sensor, though it is a camera of the same model. In this paper, we have adjusted the distribution of the overall brightness value of the image to compensate for this difference. As a result, the average deviation was the maximum of (Indoor: 6.89, outdoor: 24.23), we obtained images with almost no deviation (Indoor: maximum 0.42, outdoor: maximum: 2.73). In the future, we will study and apply more accurate image analysis methods than image brightness distribution.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.997-1007
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• 2015

In this paper, we propose a method for automatically analyzing the bone formation in a mouse model of frontal bone defect. We perforate two holes of 0.8mm diameter in the frontal bone and observe the bone formation process using a micro CT. Because the conventional analysis software of the micro CT does not support automatic analysis of the bone formation status, we have to use a manual analysis method. However the manual analysis is very cumbersome and requires a lot of time, we propose an automatic analysis method. It rotates the image around three axes directions so that the mouse's skull come into regular position. It calculates the cumulative image of the voxel values for the perforated bone surface. It estimates the hole location by finding the darkest point in the cumulative image. The proposed method was applied to 24 CT images of saline administration group and PTH administration group and hole location was estimated. BV/TV index was calculated for the estimated hole to evaluate the bone formation status. Experimental results showed that bone formation process is more active in PTH administration group. The method proposed in this paper could replace successfully the cumbersome and time consuming manual job.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.318-322
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• 1997

A prototype of combustion zone monitoring system as been developed and installed into tuyeres of the blast furnace. The system consists of CCD(charge coupled device) cameras, sonic flow meters, an image processor and a personal computer. The personal computer collects raceway luminance data and operational data from the image processor that is connected to the color CCD camera from the blast furnace process computer, respectively. In addition, the sonic flow meters supply coal injection rate data to the personal computer. Then, the personal computer evaluates the combustion conditions with the raceway inspection algorithm. This integrated monitoring system allows us to detect abnormal raceway conditions and the clogging status of coal injection pipe. The image processing techniques of the system enable us to effectively monitor unburnt coal sticking to tuyere tip and injection lance wear conditions. Such a developed system ensures rapid and precise raceway inspection. The image processing capability of the system has helped operator to early detect both the unburnt coal sticking problem and the errosion problem of injection lance. Furthermore, the system could control the abnormal raceway condition based the the analysis results obtained from combustion monitoring.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.623-629
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• 2004

In this paper, a Efficient method for the mixed image separation is presented using independent component analysis and the new fast expectation-maximization(EM) algorithm. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme in various applications. However, it has been known that ICA does not establish good performance in source separation by itself. So, Innovation process which is one of the methods that were employed in image separation using ICA, which produces improved the mixed image separation. Unfortunately, the innovation process needs long processing time compared with ICA or EM. Thus, in order to overcome this limitation, we proposed new method which combined ICA with the New fast EM algorithm instead of using the innovation process. Proposed method improves the performance and reduces the total processing time for the Image separation. We compared our proposed method with ICA combined with innovation process. The experimental results show the effectiveness of the proposed method by applying it to image separation problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6069-6091
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• 2017

Augmented Reality (AR) overlays virtual information on real world data, such as displaying useful information on videos/images of a scene. This paper presents an Enhanced AR (EAR) system that displays useful statistical players' information on captured images of a sports game. We focus on the situation where the input image is degraded by strong sunlight. Proposed EAR system consists of an image enhancement technique to improve the accuracy of subsequent player and face detection. The image enhancement is followed by player and face detection, face recognition, and players' statistics display. First, an algorithm based on multi-scale retinex is proposed for image enhancement. Then, to detect players' and faces', we use adaptive boosting and Haar features for feature extraction and classification. The player face recognition algorithm uses boosted linear discriminant analysis to select features and nearest neighbor classifier for classification. The system can be adjusted to work in different types of sports where the input is an image and the desired output is display of information nearby the recognized players. Simulations are carried out on 2096 different images that contain players in diverse conditions. Proposed EAR system demonstrates the great potential of computer vision based approaches to develop AR applications.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.204-214
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• 2017

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

• Journal of the Semiconductor & Display Technology
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• v.10 no.3
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• pp.89-94
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• 2011

The image identification methodology associates an image with a unique identifiable representation. Whenever the methodology regenerates an identifier for the same image, moreover, the newly created identifier needs to be consistent in terms of representation value. In this paper, we discuss a methodology for image identifier generation utilizing luminance correlation. We furthermore propose a method for performance enhancement of the image identifier generation. We also demonstrate the experimental evaluations for uniqueness and similarity analysis and performance improvement that have shown favorable results.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.04a
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• pp.692-697
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• 2000

멀티미디어 개인 휴대 통신(MPCS)에서 다중 클래스호에 대한 효율적인 채널할당은 매우 중요하다고 할 수 있다. 본 논문에서는 Image/Voice/Data 호에 대하여 가변적 보호 채널을 할당하는 새로운 방식을 제안하였다. 이러한 방식은 3차원 상태 천이도로 모델링 되며 보호 채널의 크기를 가변적으로 조절함으로써 보다 융통성있는 서비스를 제공하게 되며, 또한 수학적 분석과 시뮬레이션을 통해 비교분석을 수행하였다.