• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제52권7호
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• pp.434-434
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• 2003

This paper proposes a new quantitative and objective image quality metric which is essential to verify the performance of block-based DCT image coding The proposed metric considers not only global distortion of coded image such as spatial frequency sensitivity and channel masking using HVS based multi-channel model, but also structural distortions caused block-based coding. The experimental results show a strong correlation between propose(B metric and subjective metric.

• 대한방사선기술학회지:방사선기술과학
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• 제41권6호
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• pp.595-602
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• 2018

Quality control (QC) of Computed Tomography (CT) devices is based on image quality measurement on AAPM CT phantom which is a standard phantom. Although it is possible to control the accuracy of the CT apparatus, it is expensive and has a disadvantage of low penetration rate. Therefore, in this study, we make image quality measurement phantom at low cost using FFF (Fused Filament Fabrication) type three-dimensional printer and try to analyze the usefulness, compare it with existing standard phantom. To print a phantom, We used three-dimensional printer of the FFF system and PLA (Poly Lactic Acid, density: $1.24g/cm^3$) filament, and the CT device of 64 MDCT (Aquilion CX, Toshiba, Japan). In addition, we printed a phantom using three-dimensional printer after design using various tool based on existing standard phantom. For image quality evaluation, AAPM CT phantom and self-generated phantom were measured 10 times for each block. The measured data were analyzed for significance using the Mannwhiteney U-test of SPSS (Version 22.0, SPSS, Chicago, IL, USA). As a result of the analysis, phantom fabricated with three-dimensional printer and standard phantom showed no significant difference (p>0.05). Furthermore, we confirmed that image quality measurement performance of a phantom using three-dimensional printer is similar to the existing standard phantom. In conclusion, we confirmed the possibility of low cost phantom fabrication using three dimensional printer.

• International Journal of Quality Innovation
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• 제5권1호
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• pp.68-84
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• 2004

The measured values of a same object should remain constant regardless of the object's position in the image. In other words, its measured values should not vary as its position in the image changes. However, lens' image distortion, heterogeneous light source, varied angle between the measuring apparatus and the object, and different surroundings where the testing is set up will all cause variation in the measurement of the object when the object's position in the image changes. This research attempts to compensate the machine vision image distortion caused by the object's position in the image by developing the compensation table. The compensation is accomplished by facilitating users to obtain the correcting object and serves the objective of improving the precision of measurement.

• 반도체디스플레이기술학회지
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• 제7권1호
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• pp.11-16
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• 2008

Confocal scanning microscopy is a widely used technique for three dimensional measurements because it is characterized by high resolution, high SNR and depth discrimination. Generally an image is generated by moving one optical probe that satisfies the confocal condition on the specimen. Measurement speed is limited by movement speed of the optical probe; scanning speed. To improve measurement speed we increase the number of optical probes. Specimen region to scan is divided by optical probes. Multi-point information each optical probe points to can be obtained simultaneously. Therefore image acquisition speed is increased in proportion to the number of optical probes. And multiple optical probes from red, green and blue laser sources can be used for color imaging and image quality, i.e., contrast, is improved by adding color information by this way. To conclude, this technique contributes to the improvement of measurement speed and image quality.

• 방송공학회논문지
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• 제16권2호
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• pp.319-330
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• 2011

스테레오스코픽 3D 영상의 객관적인 화질 평가를 위해서 지금까지는 왼쪽과 오른쪽 영상에 대해 각각 2D 영상의 화질을 측정, 평가하는 방법을 사용하였다. 하지만 이 방법은 각각의 영상에 대해서 별도로 화질을 평가해야 하는 불편함이 따랐다. 그래서 본 논문에서는 왼쪽과 오른쪽 영상을 중첩하여 만든 하나의 영상을 통하여 스테레오스코픽 3D 영상의 화질을 평가하는 방법을 제안하여, 보다 간편하고 빠르게 스테레오스코픽 3D 영상의 화질을 평가할 수 있도록 하였다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.119-124
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• 2001

In this study, a vision system with image processing method have been introduced to find the edge radius of curvature. It was applied to inspect the edge quality of the deburring process product with brush grinding. Size of data was found to be critical in calculating the radius of curvature. Results using laser measurement system were compared.

• 품질경영학회지
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• 제23권2호
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• pp.1-9
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• 1995

Two user groups, expert and non-expert, are sampled to measure the image quality of G3 facsimile. A ITU-TS tset chart No. 2 has been transmitted among some selected cities and evaluated by user groups. Their subjective evaluation to the image quality is quantified by Mean Opinion Score method. There is highly significant difference in the image quality between expert and non-expert. From modified logit model, it is concluded that there is no significance in two considered factors, the effects of the number of links and transmission time. The derived percent curves show that 80% of non-experts(90% of expert) is considering the image quality of G3 facsimile "fair, good, or excellent".

• Journal of Information Technology Applications and Management
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• 제25권2호
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• pp.41-52
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• 2018

This paper presents a method for accurate camera self-calibration based on SIFT Feature Detection and image quality assessment. We performed image quality assessment to select high quality images for the camera self-calibration process. We defined high quality images as those that contain little or no blur, and have maximum contrast among images captured within a short period. The image quality assessment includes blur detection and contrast assessment. Blur detection is based on the statistical analysis of energy and standard deviation of high frequency components of the images using Discrete Cosine Transform. Contrast assessment is based on contrast measurement and selection of the high contrast images among some images captured in a short period. Experimental results show little or no distortion in the perspective view of the images. Thus, the suggested method achieves camera self-calibration accuracy of approximately 93%.

• 대한전자공학회논문지SP
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• 제46권1호
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• pp.32-40
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• 2009

본 논문에서는 단말기상의 출력영상을 기반으로 한 수신영상 복원 방법을 제안한다. 무선 네트워크를 통해 전송되는 비디오 스트리밍의 화질을 평가하기 위해서는 단말기로 전송된 수신 영상에 대한 정보가 필요하다. 그러나 실제 전송된 스트리밍 데이터를 단말기로부터 얻기가 용이하지 않기 때문에 일반적으로 다수의 사람이 직접 화질을 평가하는 방법이 많이 사용된다. 본 논문에서는 단말기로 수신된 스트리밍 영상을 획득하기 위하여 단말기 상에서 출력되는 영상을 기반으로 전송영상을 재구성한다. 이를 위하여 제안한 방법에서는 단말기를 통해 출력되는 영상을 카메라를 이용하여 획득하고, 획득된 영상에서 나타나는 카메라와 단말기 사이의 기하학적 왜곡과 컬러 왜곡을 모델링하여 제거함으로써 전송받은 영상을 재구성하였다. 실험 결과에서는 원영상과 재구성한 영상사이의 PSNR을 측정하여 알고리즘의 성능을 평가하였다. 그 결과 제안한 알고리즘을 통해 $27{sim}28dB$의 PSNR을 얻을 수 있었다. 또한 EPSNR을 이용하여 제안한 알고리즘의 성능을 분석한 결과, 제안한 알고리즘을 통하여 예측된 영상이 MOS 테스트 스케일에서 비교적 좋은 범위에 속하는 것을 확인하였다.

• Journal of Information Processing Systems
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• 제18권2호
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• pp.223-234
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• 2022

The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.