• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.7
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• pp.739-745
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• 2014

In this paper, an evaluation of intelligent CCTV system is proposed with recording and implementation video and video DB. Videos for evaluation are recorded by dividing far, mid and near zone. Video DB has video recording information, detection area, and ground truth in XML format. A video annotation tool is proposed to make ground truth effectively in this paper. A video annotation tool writes ground truths of videos and includes evaluation comparing system alarms with ground truths.

• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.33-37
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• 2004

고해상 입체 위성영상 엄밀 모델링(Rigorous Modeling)을 구현하고, 이를 기반으로 각 입체시 영상을 제작하여 3차원 정확도 평가를 수행하였다. 본 연구 지역으로 진주지역의 SPOTS 입체영상을 이용하였으며, 각 영상별 기준점 자료는 1/5000 수치지도를 이용하여 입체영상의 중복영역 내에 균등하게 지상기준점 40점을 추출하였다. 추출된 점을 각각 기준점과 검사점으로 구분하여 엄밀 모델링의 정확도를 분석하였다. 또한, 입체시 제작시에 기준점으로 사용된 지상좌표와 이에 대응하는 영상점을 이용하여 입체시 영상을 제작하였다. 제작된 입체시 영상에서 동일점을 획득하기 위해 영상 매칭 및 수치해석도화기(Helava System)를 이용하여 정확한 영상점을 획득하여 3차원 좌표를 계산하여 정확도 평가를 수행하였다.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.552-560
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• 2011

In this paper, a new no-reference sharpness measure using frequency domain coefficients is proposed. Although most existing sharpness measures used pixel intensity to compute the blur degree, the proposed sharpness measure computes the sharpness using frequency coefficients. To assess the perceived sharpness of a given image, the image is re-blurred by a Gaussian low pass filter and a new quality measure function was defined using the frequency domain coefficients of the given image and the re-blurred image. To evaluate the proposed algorithms, TID2008 quality assessment database was used. Experimental results show that the proposed quality assessment method showed high correlation with the subjective scores.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.51-58
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• 2021

Three degrees of freedom plus(3DoF+) and six degrees of freedom(6DoF) system, which supports a user's movements in graphical and natural scene-based virtual reality, requires multiple high-quality and high-resolution videos to provide immersive media. Previous video quality assessment methods are not appropriate for the 3DoF+ and 6DoF system assessment because different types of artifacts occur in these systems which are not shown in the traditional video compression. This paper provides the performance assessments of several quality assessment methods in 3DoF+ system. Furthermore, this paper presents a super metric, which combines multiple quality assessment methods, thereby it showed a higher correlation coefficient with the subjective quality assessment than the previous methods. Experimental results on 3DoF+ immersive video showed 0.4513 gain on correlation coefficient with subjective quality assessment compared to that of peak signal-to-noise ratio(PSNR).

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.257-274
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• 2021

Although image segmentation is a critical part of object-based analysis of high resolution imagery, there has been lack of studies to evaluate the quality of image segmentation. In this study, we aimed to find practical and effective methods to obtain optimal parameters for image segmentation. Evaluations of image segmentation are divided into unsupervised, supervised, and qualitative visual interpretation methods. Using the multispectral UAV images, sampled from urban and forest over the Incheon Metropolitan City Park, three evaluation methods were compared. In overall, three methods showed very similar results regardless of the computational costs and applicability, although the optimal parameters determined by the evaluations were different between the urban and forest images. There is no single measure that outperforms in the unsupervised evaluation. Any combinations of intra-segment measures (V, COV, WV) and inter-segment measures (MI, BSH, DTNP) provided almost the same results. Although supervised method may be biased by subjective selection of reference data, it can be easily applied to detect object of interest. The qualitative visual interpretation on the segmentation results corresponded with the unsupervised and supervised evaluations.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.604-606
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• 2002

본 논문에서는 홍채인식 시스템에서의 성능 향상을 위하여, 고정 초점 카메라로부터 획득된 영상을 평가하여 인식과정에서 효과적으로 다루어질 수 있는 영상을 선택하는 방법을 제안한다. 획득된 영상이 여과 없이 사용되는 경우 홍채 인식 시스템의 신뢰도 및 성능 저하의 중요 요인으로 작용됨으로 인식 부적합 영상의 몇 가지 형태를 기준으로 영상 판별과정을 거친 후 인식 과정에 영상을 제공하는 과정이 필수적이다. 본 논문에서 제안한 영상 평가 방법은 실제 홍채 인식 시스템에 적용한 결과 시스템의 신뢰도와 성능을 향상시킬 수 있었다.

• Progress in Medical Physics
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• v.19 no.4
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• pp.201-208
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• 2008

Physical evaluations provide the basis for an objective and quantitative analysis of the image quality. Nonetheless, there are limitations in using physical evaluations to judge the utility of the image quality if the observer's subjectivity plays a key role despite its imprecise and variable nature. This study proposes a new method for objective and quantitative evaluation of image quality to compensate for the demerits of both physical and subjective image quality and combine the merits of them. The images of chest phantom were acquired from four digital radiography systems on clinic sites. The physical image quality was derived from an image analysis algorithm in terms of the contrast-to-noise ratio (CNR) of the low-contrast objects in three regions (lung, heart, and diaphragm) of a digital chest phantom radiograph. For image analysis, various image processing techniques were used such as segmentation, and registration, etc. The subjective image quality was assessed by the ability of the human observer to detect low-contrast objects. Fuzzy integral was used to integrate them. The findings of this study showed that the physical evaluation did not agree with the subjective evaluation. The system with the better performance in physical measurement showed the worse result in subjective evaluation compared to the other system. The proposed protocol is an integral evaluation method of image quality, which includes the properties of both physical and subjective measurement. It may be used as a useful tool in image evaluation of various modalities.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.284-291
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• 2013

The importance of ultrasound examination in the field of medical imaging has been emphasized and the interest in sonographic image evaluation is growing. However image evaluations by the non-standardized criteria and methods, so establishment of legal provisions and objective evaluation criteria are needed. In this study, we used SNR to find out more quantitative way and supplement the limitations of the existing phantom image evaluation. The results of acquired 8 images using ATS-539 multipurpose phantom were compared in SNR of sensitivity and gray-scale dynamic range. In the result of the experiment, excellent equipment of existing phantom images are G1, S1 and G2 in regular sequence. In SNR of sensitivity, G1, S1 and G2 and in SNR of gray-scale dynamic range, S1 G1 and G2 in order. In the conclusion, all the experiment results did not show big difference and regular pattern neither. Therefore, the new evaluation measures should be used with the existing phantom image evaluation method for more objective and quantitative evaluation of the ultrasound imaging device.

• The Transactions of the Korea Information Processing Society
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• v.2 no.4
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• pp.524-534
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• 1995

Image segmentation is a process of partitioning of an image into different regions that have similar properties. It is an old and difficult problem. They have developed many image segmentation systems and have studied to evaluate the existing segmentation systems. However, evaluation of image segmentation systems is very difficult in nature. In this paper, we propose the evaluation criteria that evaluate image segmentation systems automatically. In order to overcome the drawbacks of using only a single evaluation criterion, we have incorporated four evaluation criteria, that is, boundary difference, boundary consistency, region uniformity, and region difference. As the experimental results show, our evaluation criteria performs very well.

• Journal of the Korea Computer Graphics Society
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• v.28 no.2
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• pp.11-19
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• 2022

Recently, various researches on medical image generation have been suggested, and it becomes crucial to accurately evaluate the quality and diversity of the generated medical images. For this purpose, the expert's visual turing test, feature distribution visualization, and quantitative evaluation through IS and FID are evaluated. However, there are few methods for quantitatively evaluating medical images in terms of fidelity and diversity. In this paper, images are generated by learning a chest CT dataset of non-small cell lung cancer patients through DCGAN and PGGAN generative models, and the performance of the two generative models are evaluated in terms of fidelity and diversity. The performance is quantitatively evaluated through IS and FID, which are one-dimensional score-based evaluation methods, and Precision and Recall, Improved Precision and Recall, which are two-dimensional score-based evaluation methods, and the characteristics and limitations of each evaluation method are also analyzed in medical imaging.