• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.96.5-96
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• 2002

This paper describes extraction procedures for the center coordinates of steam generator tubes of Youngkwang nuclear power plant No. 6 unit. The centering coordinates of tubes are needed for monitoring whether ECT probe is exactly inserted into tube or not. However, The tube image tends to have poor contrast because steam generator bowl is sealed. The centering coordinates extraction procedure consists of two steps. The first step is to process the region with high contrast in entire image of steam generator tubes. Using the center points extracted in the first step and the geometry of tubes lined up in regular triangle patterns the centering coordinates of the rest region with low contrast...

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.309-310
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• 2006

This paper presents an enhanced algorithm for compensating the visual quality in backlight image. Current cameras do not represent all details of scene into human's eye. Saturation and underexposure are common problems in backlight image. Retinex algorithm, derived from Land's theory on human visual perception is known to be effective in enhancing the contrast. However, its weaknesses are long processing time and low contrast of bright area in backlight scene because of compensating the details of dark area. In this paper, K-Retinex algorithm is proposed to reduce the processing time and enhance the contrast in both dark and bright area. To show the superiority of proposed algorithm, we compare the processing time and local variance of each area above.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1904-1926
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• 2016

Iris recognition for biometric personnel identification has gained much interest owing to the increasing concern with security today. The image quality plays a major role in the performance of iris recognition systems. When capturing an iris image under uncontrolled conditions and dealing with non-cooperative people, the chance of getting non-ideal images is very high owing to poor focus, off-angle, noise, motion blur, occlusion of eyelashes and eyelids, and wearing glasses. In order to improve the accuracy of iris recognition while dealing with non-ideal iris images, we propose a novel algorithm that improves the quality of degraded iris images. First, the iris image is localized properly to obtain accurate iris boundary detection, and then the iris image is normalized to obtain a fixed size. Second, the valid region (iris region) is extracted from the segmented iris image to obtain only the iris region. Third, to get a well-distributed texture image, bilinear interpolation is used on the segmented valid iris gray image. Using contrast-limited adaptive histogram equalization (CLAHE) enhances the low contrast of the resulting interpolated image. The results of CLAHE are further improved by stretching the maximum and minimum values to 0-255 by using histogram-stretching technique. The gray texture information is extracted by 1D Gabor filters while the Hamming distance technique is chosen as a metric for recognition. The NICE-II training dataset taken from UBRIS.v2 was used for the experiment. Results of the proposed method outperformed other methods in terms of equal error rate (EER).

• Korean Journal of Radiology
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• 제22권1호
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• pp.131-138
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• 2021

Objective: Iterative reconstruction degrades image quality. Thus, further advances in image reconstruction are necessary to overcome some limitations of this technique in low-dose computed tomography (LDCT) scan of the chest. Deep-learning image reconstruction (DLIR) is a new method used to reduce dose while maintaining image quality. The purposes of this study was to evaluate image quality and noise of LDCT scan images reconstructed with DLIR and compare with those of images reconstructed with the adaptive statistical iterative reconstruction-Veo at a level of 30% (ASiR-V 30%). Materials and Methods: This retrospective study included 58 patients who underwent LDCT scan for lung cancer screening. Datasets were reconstructed with ASiR-V 30% and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The objective image signal and noise, which represented mean attenuation value and standard deviation in Hounsfield units for the lungs, mediastinum, liver, and background air, and subjective image contrast, image noise, and conspicuity of structures were evaluated. The differences between CT scan images subjected to ASiR-V 30%, DLIR-M, and DLIR-H were evaluated. Results: Based on the objective analysis, the image signals did not significantly differ among ASiR-V 30%, DLIR-M, and DLIR-H (p = 0.949, 0.737, 0.366, and 0.358 in the lungs, mediastinum, liver, and background air, respectively). However, the noise was significantly lower in DLIR-M and DLIR-H than in ASiR-V 30% (all p < 0.001). DLIR had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than ASiR-V 30% (p = 0.027, < 0.001, and < 0.001 in the SNR of the lungs, mediastinum, and liver, respectively; all p < 0.001 in the CNR). According to the subjective analysis, DLIR had higher image contrast and lower image noise than ASiR-V 30% (all p < 0.001). DLIR was superior to ASiR-V 30% in identifying the pulmonary arteries and veins, trachea and bronchi, lymph nodes, and pleura and pericardium (all p < 0.001). Conclusion: DLIR significantly reduced the image noise in chest LDCT scan images compared with ASiR-V 30% while maintaining superior image quality.

• 전자공학회논문지
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• 제53권10호
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• pp.77-83
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• 2016

본 논문에서는 칼라 영상의 대조비 개선을 위한 비대칭도 특성을 이용한 적응적인 대조비 개선 레티넥스 방식을 제안한다. 입력 영상 휘도 성분의 저조도 정도를 예측하기 위해 휘도 성분의 비대칭도 함수로 표현되는 매개변수를 정의하고, 정의된 매개 변수 및 예측 반사 성분을 이용하여 반사 성분을 보정하기 위한 비선형 함수를 제안한다. 더불어, 추정된 반사 성분의 통계 특성을 이용하여 비선형 함수의 이득 및 오프셋을 결정하는 방식에 대해 기술한다. 연산량 절감을 위해 색차 성분의 보정 과정을 위해 입력 영상의 휘도 성분과 보정된 휘도 성분을 이용한다. 실험을 통해 색신호 성분의 대조비 및 색신호 왜곡의 개선이 효과적으로 이루어짐을 확인할 수 있었다.

• 대한임베디드공학회논문지
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• 제12권2호
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• pp.97-103
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• 2017

Thermal imaging is mainly used in military equipment required for night observation. In particular, technologies of uncooled thermal imaging detectors are being developed as applied to low-cost night observation system. Many system integrators require different specifications of the uncooled thermal imaging camera but their development time is short. In this approach, EOSYSTEM has developed a small size, TEC-less uncooled thermal imaging camera module with $32{\times}32mm$ size and low power consumption. Both domestic detector and import detector are applied to the EOSYSTEM's thermal imaging camera module. The camera module contains efficient infrared image processing algorithms including : Temperature compensation non-uniformity correction, Bad/Dead pixel replacement, Column noise removal, Contrast/Edge enhancement algorithms providing stable and low residual non-uniformity infrared image.

• 한국산학기술학회논문지
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• 제14권3호
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• pp.1378-1387
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• 2013

히스토그램 평활화는 영상의 밝기 분포를 변화시킴으로써 화질을 향상시키는 방법으로 다양한 분야에서 응용되고 있다. 전역적인 방법은 영상 밝기의 전체적인 분포를 균등 분포로 변환함으로써 영상의 밝기가 과도하게 변하는 단점을 갖고 있다. 이를 해결하기 위한 방법으로 K. Zuierveld가 제안한 대비 제한 적응 히스토그램 평활화(CLAHE)가 실용적으로 널리 사용되고 있다. 이 방법에서는 블록단위의 처리를 위한 블록 크기와 대비 제한을 위한 매개변수 등 두 개의 매개변수가 히스토그램의 평활화 성능을 결정하는데, 이것들을 결정하는 구체적인 알고리듬은 없으며 실험적으로 시행착오학습 통해 결정한다. 본 논문에서는 영상의 엔트로피에 기반해서 CLAHE의 매개변수인 블록 크기와 대비제한 매개변수를 결정하는 새로운 방법을 제안한다. 제안한 방법은 CLAHE를 자동화할 수 있으며, 전체적으로 어두운 영상이나 밝은 영상에 적용한 결과 전역적인 방법에 비해 주관적 화질 개선의 효과를 나타내었다.

• International Journal of Contents
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• 제5권2호
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• pp.26-31
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• 2009

This paper describes a new image watermarking scheme invariant to rotation, scaling and translation (RST) attacks. For obtaining the invariance properties we propose to present an image of watermark by wedges and rings to convert its rotation to shift and then utilize the shift invariance property of the Direct Fourier Transform (DFT). But in contrast to conversional schemes based on the Fourier-Mellin transform (FMT), we do not use a log-polar mapping (LPM). As a result, our scheme preserves high quality of original image since it is not underwent to LPM For withstanding against JPEG compression, noise addition and low-pass (LP) filtering attacks a low frequency watermark is embedded into middle frequencies of the original image. Experiments with various attacks show the robustness of the proposed scheme.

• 디지털산업정보학회논문지
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• 제15권1호
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• pp.99-107
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• 2019

Retinex-based image enhancement is a technique that utilizes the property that the human visual characteristics are sensitive to the difference from the surrounding pixel value rather than the pixel value itself. These Retinex-based algorithms show different characteristics of the improved image depending on the applied color space or gamma correction. In this paper, we set eight different experimental conditions according to the application of color space and gamma correction, and analyze the objective and subjective performance of each Retinex based image enhancement algorithm and apply it to the implementation of Retinex based algorithm. In the case of gamma correction, quantitative low entropy images and low contrast images are obtained. The application of Retinex technique in HSI color space rather than RGB color space is found to be high in overall subjective image quality as well as maintaining color.

• 한국융합학회논문지
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• 제7권6호
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• pp.1-6
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• 2016

본 논문에서는 영상을 분할하고, 분할된 영상의 로컬 히스토그램을 이용하여 저조도 환경의 블랙박스 영상 향상 방법을 제안한다. 기존 블랙박스 영상은 저조도 환경에서 촬영되기 때문에 향상 기법을 적용 시 과도한 향상 효과가 발생하는 단점이 있다. 제안 알고리즘은 3단계 과정으로 구성된다. 1단계는 입력 영상을 ($N{\times}M$)개 조각으로 분할하고, 분할된 부분 영상과 인접한 부분 영상을 그룹 영상으로 묶어 구분한다. 2단계는 구분된 그룹 영상을 각각의 로컬 히스토그램을 이용하여 명암 향상 처리를 수행한다. 3단계는 명암 향상 처리된 각각의 그룹 영상의 특성을 반영한 전달 함수를 이용하여 전체 영상을 재구성한다. 알고리즘 검증을 위하여 지하 주차장과 야간 운행 영상을 저조도 환경 영상으로 사용하였다. 제안 알고리즘은 다양한 저조도 환경의 블랙박스 영상을 향상시켜 차량 운행 환경 정보 획득에 유리한 영상을 제공할 수 있다.