• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.32-34
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• 2007

The X-ray projection system has long been used for steel-tube inspection and weld monitoring. The thickness of tubes and welded areas is based on the evaluation of radiographic shadow projections. The traditional tangential measurement estimates the distance of border lines of the projected wall shadows of a tube onto a radiographic image detector. The detected image in which although there is a variety of noise may be sectioned into several partitions according to its specific blocks. Imaging noise originates from most of elements of the system, such as shielding CCD camera, imaging screen, X-ray source, inspected object, electronic circuits and etc. The tangential projection incorrectness and noise influence on imaging quality. In this paper we first sectionalize the X-ray image on the basis of vertical contrast difference. And next functional and statistic analysis are carried on at each region. Geometrical distance and unsharpness of the edge caused by visual evaluation uncertainties are also discussed.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.812-819
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• 1996

This study was performed to quantify microscopically morphological characteristics of cotton fiber to identify parameters for quality evaluation using image analysis . The image of each fiber was captured by a Pc-based color imaging system using a conventional microscope. Ends of individual cotton fibers were glued on a microscope slide without any tension or straightening. A modified watershed technique was implemented to identify individual convolution segments, which were defined as sections of the fiber bordered by two neighboring convolutions. Length, area and perimeter of each convolution segment were measured directly from the image . Average width, shape factor and number of convolution segments in mm were calculated from the measured parameters. The performance of the image analysis algorithm was compared with visual varieties of cotton . The image analysis results agreed with visual inspection in 89.6% of the tested images.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2567-2571
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• 2023

Scintillator materials are widely used in the medical and industrial fields for imaging systems using gamma cameras. In this study, image evaluation is performed by modeling a gamma camera system based on a lutetium-yttrium oxyorthosilicate (LYSO) scintillation detector using a pinhole collimator that can improve the spatial resolution. A LYSO detector-based gamma camera system is modeled using a Monte Carlo simulation tool. The geometric concept of the pinhole collimator is designed using various magnification factors, and the spatial resolution is measured using the acquired source image. To evaluate the resolution, the full width at half maximum (FWHM) and natural image quality assessment (NIQE), a no-reference-based parameter, are used. We confirm that the FWHM and NIQE values decrease simultaneously when the diameter of the pinhole collimator increases. Additionally, we confirm that the spatial resolution improves as the magnification factor increases under the same pinhole diameter condition. Particularly, a 0.57 mm FWHM value is obtained using the modeled gamma camera system with a LYSO scintillation detector. In conclusion, our results demonstrate that a pinhole collimator with a LYSO scintillation detector is a promising gamma camera imaging system.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2594-2600
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• 2020

A gamma camera system using radionuclide has a functional imaging technique and is frequently used in the field of nuclear medicine. In the gamma camera, it is extremely important to improve the image quality to ensure accurate detection of diseases. In this study, we designed a blind-deconvolution framework after a noise-reduction algorithm based on a non-local mean, which has been shown to outperform conventional methodologies with regard to the gamma camera system. For this purpose, we performed a simulation using the Monte Carlo method and conducted an experiment. The image performance was evaluated by visual assessment and according to the intensity profile, and a quantitative evaluation using a normalized noise-power spectrum was performed on the acquired image and the blind-deconvolution image after noise reduction. The result indicates an improvement in image performance for gamma camera images when our proposed algorithm is used.

• Proceedings of the Petrological Society of Korea Conference
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• 2009.05a
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• pp.135-135
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• 2009

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.168-189
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• 1996

In order for the corporation to get a good image from the customers it should consider several variables, but especially important are corproate ethics and customer satisfaction through quality improvement. Standard multivariate data analysis can be applied to find out the importance of customer satisfaction and corporate ethics as influence factors in the corporate competitive strategy. When applying this Methodology, multivariate normal distributions density function and the identical covariance between groups assumptions have to be satisfied. By using the evaluation result from a small number of specialists in an attempt to decide on the strategical factors that will create a better company image than its competitor, if it chooses to use statistical discriminant analysis method, it would be difficult to satisfy the two assumptions mentioned above. This thesis introduces discriminant analysis method that uses LP/GP effectively which is applicable to this particular situation.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.863-864
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• 2008

To predict the iris matching performance and guarantee its reliability, image quality measure prior to matching is desired. An analysis on iris image degradation factors which deteriorate matching performance is a basic step for iris image quality measure. We considered five degradation factors-white-out, black-out, noise, blur, and occlusion by specular reflection-which happen generally during the iris image acquisition process. Experimental results show that noise and white-out degraded the EER most significantly, while others on EER were either insignificant or degradation images resulted in even better performance in some cases of blur. This means that degradation factors that affect the performance can be different from those based on human perception or image degradation evaluation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.32-40
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• 2009

In this paper, we proposed an reconstruction algorithm of transmitted frames from displayed image on video terminal. For image quality assessment of the video streaming in the wireless network, we need information of the image that is transmitted to the end-user's device. Generally, subjective methods are widely used to evaluate the image quality by human beings because it is difficult to extract the transmitted image from the end-user's device. This paper presents an image reconstruction algerian based on the displayed image in video terminal for the extraction of the transmitted image. In the proposed method, we acquired the displayed image on video terminal using the camera. Camera-acquired images exhibit geometric and color distortions caused by characteristics of cameras and display devices. Therefore we correct the geometric distortion by exploiting the homography and color distortion by pre-computed look-up table. The experimental results show that the proposed measurement system yields promising estimation performance in terms of PSNR of $27{\sim}28dB$. We also carried out performance evaluation of the proposed method in terms of EPSNR and the quality of the estimated images by the proposed algerian was in fairly good range of MOS test scale.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.997-1004
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• 2007

High resolution synthetic aperture radar image could be sensitive to the various parameters of the payload, platform, and ground system. In this paper, a parameter based SAR simulator is presented for two-dimensional image formation and image quality analysis. Functional modules are implemented by Matalb code and GUI for the flexibility and expandability. Main function of this simulator includes the SAR input signal generation, range-doppler algorithm(RDA) based SAR image formation, and the SAR image quality analysis which is relevant to the SAR system design parameters. This simulator can effectively be used for the SAR image quality performance evaluation, which can be applicable to the airborne as well as spaceborne SAR system design and analysis.