• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.324-332
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• 2004

In image communications related to web browsing, image database, and telemedicine, image data processing on the region of interest (ROI) for providing the primary information is needed in the view of saying search time and bandwidth. In this paper, an enhanced algorithm for processing image data that involves multiple ROIs is presented in order to increase PSNR vs. compression ratio performance above the previous JPEG2000 Part1 Maxshift method. Since the wavelet transform enables us to a progressive transmission mechanism, Multiple-ROI coding is possible to compress, transmit, and reconstruct the image data with a better quality than those of non-ROI method while the required transmission bandwidth is kept relatively low.

• The Journal of Society for e-Business Studies
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• v.11 no.1
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• pp.91-112
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• 2006

Unlike typical corporate investments, IT expenditures have direct impact on many aspects of a business, including those that are difficult to quantify. Therefore, financial indicators alone do not do justice to the full effect of an If investment. Proposed in this paper is a methodology to measure the return on IT investments, including non-financial impacts expressed in terms of monetary values. This methodology shows tangible cost as well as hidden cost by analyzing total cost of ownership. The methodology also produces ROI by performing cost benefit analysis including financial and non-financial factors. This paper suggests a more objective validation of If's impact on the business activities. It rationalizes investment priorities and provides a systematic approach to effective IT investment.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.709-712
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• 2009

대부분의 고속도로 안개경고시스템은 시정측정을 위해 고가의 광학센서를 사용하고 있으나 운전자의 시정감각과 유사하면서도 비교적 저가인 CCTV를 이용한 시정측정에 관한 연구가 활발히 이루어지고 있다. 그러나 대부분의 CCTV를 이용한 시정측정 방법은 ROI를 기반으로 하고 있어 설치가 까다롭고 기존 CCTV를 활용하기 어렵다는 문제점을 가지고 있다. 본 논문에서는 고속도로상의 안개경고는 약 1~2Km이내의 시정일 때 발생되며, 눈으로 물체를 식별할 수 있는 최대거리가 시정이라는 기초적인 개념에 근거하여 고속도로 안개경고시스템에 사용될 수 있는 Non-ROI 기반의 실시간 CCTV 시정측정 방법을 제안한다. 이를 위해 본 논문에서는 고속도로상에 주행중인 차량의 실시간 이동영역과 가시선을 검출하고 카메라와 도로간의 상관관계를 나타내는 도로모델을 이용하여 시정측정을 수행하는 방법을 제시한다. 제안된 방법은 1~2Km 이내의 시정측정을 위한 방법으로 ROI가 필요없고 직관적이고 현실적인 주야간 시정측정이 가능하며 기존의 고속도로 CCTV에 바로 적용할 수 있다는 장점이 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.679-686
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• 2014

Recently, users can get countless images and videos by network. So, the compression technology of image and video is researched more and more. However, the situation which is the interested range of the image is occurred. For instance, since the region of face is more important than background, the image compression technology bases on the region of interest (ROI) is necessary, in the ATM environment. In this research, given the human visual system, which are not sensitive to illumination variations at very dark and light regions of image, we calculate the standard deviation of block and use this value to define the ROI. In encoding process, the relatively high quality can be obtained at the ROI and the relatively low quality can be obtained at the non ROI. In proposed scheme, the feature which is the encoding process according to subjectively image quality can be demonstrated. Finally, this proposed scheme is applied to JPEG standard. The experimental results demonstrate that proposed scheme can achieve better image quality at the high compression ratio.

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.151-159
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• 2014

Computed tomography (CT) is one of the most widely used medical imaging modality. However, substantial x-ray dose exposed to the human subject during the CT scan is a great concern. Region-of-interest (ROI) CT is considered to be a possible solution for its potential to reduce the x-ray dose to the human subject. In most of ROI-CT scans, the ROI is set to a circular shape whose diameter is often considerably smaller than the full field-of-view (FOV). However, an arbitrarily shaped ROI is very desirable to reduce the x-ray dose more than the circularly shaped ROI can do. We propose a new method to make a non-circular convex-shaped ROI along with the image reconstruction method. To make a ROI with an arbitrary convex shape, dynamic collimations are necessary to minimize the x-ray dose at each angle of view. In addition to the dynamic collimation, we get the ROI projection data with slightly lower sampling rate in the view direction to further reduce the x-ray dose. We reconstruct images from the ROI projection data in the compressed sensing (CS) framework assisted by the exterior projection data acquired from the pilot scan to set the ROI. To validate the proposed method, we used the experimental micro-CT projection data after truncating them to simulate the dynamic collimation. The reconstructed ROI images showed little errors as compared to the images reconstructed from the full-FOV scan data as well as little artifacts inside the ROI. We expect the proposed method can significantly reduce the x-ray dose in CT scans if the dynamic collimation is realized in real CT machines.

• Journal of Broadcast Engineering
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• v.13 no.6
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• pp.951-961
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• 2008

Cooperative diversity is a cooperative technique which exploits user diversity by decoding the combined signal of the relayed signal and the direct signal in wireless multi-hop networks. Using the cooperation, the performance of the network system can be improved because cooperative diversity which is very strong against the fading channels can be achieved. In this paper, we propose the technique that provides the enhanced visual quality of the reconstructed video using the cooperative diversity with the FMO which is the error resilience tool of H.264/AVC standardization over wireless networks. The eye-tracker can detect the gaze point of user and transmit the gaze information to the nodes. After receiving the gaze information of user, each node performs ROI encoding according to the received gaze information. After encoding, video sources are divided into ROI and Non-ROI. Through the simulation results, the better visual quality of the reconstructed video is achieved when ROI and Non-ROI are transmitted through different channels.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.797-798
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• 2008

Visual quality of video telephony over 3G networks is not satisfactory due to limited bandwidths. Therefore, it is worthwhile to enhance subjective visual quality based on ROI coding. In this paper, we propose a rate-control algorithm for video telephony with ROI based H.264|AVC coding. The QP values are increasingly assigned in non-ROI away from the ROI so that graceful degradation of visual quality can be achieved, which is more visually pleasant.

• Journal of Biomedical Engineering Research
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• v.37 no.2
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• pp.84-89
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• 2016

In this study, we proposed ameliorated method for region of interest (ROI) study to improve its accuracy using partial volume effect (PVE). PVE which arose in volumetric images when more than one tissue type occur in a voxel, could be used to reduce an amount of gray matter and cerebrospinal fluid within ROI of diffusion tensor image (DTI). In order to define ROIs, individual b0 image was spatially aligned to the JHU DTI-based atlas using linear and non-linear registration (http://cmrm.med.jhmi.edu/). Fractional anisotropy (FA) and mean diffusivity (MD) maps were estimated by fitting diffusion tensor model to each image voxel, and their mean values were computed within each ROI with PVE threshold. Participants of this study consisted of 20 healthy controls, 27 Alzheimer's disease and 27 normal-pressure hydrocephalus patients. The result showed that the mean FA and MD of each ROI were increased and decreased respectively, but standard deviation was significantly decreased when PVE was applied. In conclusion, the proposed method suggested that PVE was indispensable to improve an accuracy of DTI ROI study.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.253-264
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• 2009

This paper presents an algorithm, aims at practical applications, for the high speed processing and performance enhancement of lane detection base on vision processing system. As a preprocessing for high speed lane detection, the vanishing line estimation and the optimal extraction of region of interest for lane boundary (ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled. Image feature information is extracted only in the ROI-LB. Road lane is extracted using a non-parametric model fitting and Hough transform within the ROI-LB. With simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since outliers of edge at each block can be removed with clustering of edge orientation for each block within the ROI-LB, the performance of lane detection can be greatly improved. The various real road experimental results are presented to evaluate the effectiveness of the proposed method.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.36-44
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• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.