• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.292-298
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• 2019

In this paper, we show how to provide high quality image service using cloud server and image quality enhancement algorithm. In other words, based on the concept of ViVa (Video Value Addition) proposed in the paper, we propose an improved system compared to the existing streaming service by providing a high-quality video with the transmission bit rate and calculation amount necessary to serve low-quality images.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.547-559
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• 2010

Delaunay triangulation is suitable for fingerprint matching because of its robustness to rotation and translation. However, missing and spurious minutiae degrade the performance and computational efficiency. In this paper, we propose a method of combining local quality assessment and 4-category minutiae classification to improve accuracy and decrease computational complexity in matching process. Experimental results suggest that removing low quality areas from matching candidate areas and classifying minutiae improve computational efficiency without degrading performance. The results proved that the proposed algorithm outperforms the matching algorithm (BOZORTH3) provided by NIST.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.859-864
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• 2018

This paper is about image improvement - we used the contrast ratio and the outline emphasis method after synthesizing two low quality images utilized by several low definition cameras. Two raspberry cameras were used to capture each image, and then we synthesized images with MATLAB program. After applying the mean computation (alignment, geometry, and harmony) to synthesized image, we extracted the cross-space. In the experiment of this study, we identified and compared the improvement consequences of extracted, synthesized image after applying outline emphasis(unsharpmask filter, highboost filter) and increasing contrast ratio (histogram uniformity, histogram stretching) to the original images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.6-9
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• 2020

최근 몰입형 가상 현실을 제공하기 위한 360 도 영상 전송 기술이 활발히 연구되고 있다. 그러나 현재 가상현실 기기가 가지는 연산 능력 및 대역폭으로는 고화질의 360 도 영상을 전송 및 재생하기에 한계가 있다. 해당 문제점을 극복하기 위해 본 논문에서는 사용자 시점의 고화질 360 도 영상 제공을 위해 사용자 시점 타일을 추출하는 움직임 제한 타일 셋 기반 타일 추출기를 구현한다. Versatile video coding (VVC) 기반 타일 인코더를 이용해 360 도 영상에 대한 비트스트림을 생성한 후, 사용자 시점에 해당하는 타일들을 선택한다. 이후 선택된 타일들은 제안하는 타일 추출기에 의해 추출되고 전송된다. 또한, 전체 360 도 영상에 대한 저화질 비트스트림을 전송하여 갑작스러운 사용자 시점 변경에 대응한다. 제안된 타일 추출기를 기반으로 360 도 영상 전송을 수행하면, 기존 VVC 기반 시스템 대비 대비 평균 24.81%의 bjontegaard delta rate (BD-rate) 감소가 가능함을 확인하였다.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.161-162
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• 2007

본 논문에서는 인간 두뇌와 같이 패턴을 인식할 수 있는 능력을 가진 신경 회로망 모델을 구현하고, 이를 바탕으로 시중의 저렴한 화상 카메라를 이용하여 미 달러화를 인식할 수 있는 시스템을 개발하였다. 제안된 시스템은 저화질 영상에서 캡쳐된 이미지를 이진영상처리 과정을 거치게 함으로써 패턴인식의 정확성 향상을 가져올 수 있었으며, 인공지능의 대표적 알고리즘인 신경회로망을 이용하여 종류별 미 달러화의 세부적인 차이를 감지하고 화폐를 정확하게 인식할 수 있도록 하였다. 각 화폐로부터 추출해 낸 특징을 신경회로망을 통해 학습시키고, 이를 통해 미 달러화의 패턴인식 능력을 실험을 통해 확인해본 결과 90%에 가까운 높은 성공률로 정확하게 인식함을 확인할 수 있었다.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2555-2557
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• 2003

본 논문에서는 열화된 이미지상에서의 자동 패턴 분할을 위해 농담 정규화 정합(NGC)법과 다중 템플레이트를 이용하여 검사 이미지내의 각 문자의 정합 계수치 합을 이용한 문자나 패턴을 자동으로 분할(segmentation)하는 알고리즘을 제안한다. 전통적인 NGC를 사용하는 검사 알고리즘은 기준 패턴의 기하학적인 level 값에 의해 계산되어 지기 때문에 검사 이미지의 획득이 불완전하다면 정합의 부독율(reject rate)은 높아진다. 제안한 알고리즘은 가시화가 좋지 않은 영상 회득 시 문자부와 배경부를 효과적으로 자동으로 분류하며 이미지 영역내의 정보와 정규화 된 상관관계를 이용하여 실제 영상에 적용시켜 제안된 알고리즘의 검증을 목표로 한다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.2
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• pp.8-17
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• 2008

This paper proposes a robust license plate extraction method from images taken under unconstrained environments. Utilization of the color and the edge information in complementary fashion makes the proposed method deal with not only various lighting conditions, hilt blocking artifacts frequently observed in compressed images. Computational complexity is significantly reduced by applying Hough transform to estimate the skew angle, and subsequent do-skewing procedure only to the candidate regions. The true plate region is determined from the candidates under examination using clues including the aspect ratio, the number of zero crossings from vertical scan lines, and the number of connected components. The performance of the proposed method is evaluated using compressed images collected under various realistic circumstances. The experimental results show 94.9% of correct license plate extraction rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.49-60
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• 2002

We propose an algorithm for extracting the boundary of a desired object with shape information obtained from sample images. Considering global shape obtained from sample images and edge orientation as well as edge magnitude, the Proposed method composed of two steps finds the boundary of an object. The first step is the approximate segmentation that extracts a rough boundary with a probability map and an edge map. And the second step is the detailed segmentation for finding more accurate boundary based on the SEEL (seed-point extraction and edge linking) algorithm. The experiment results using IR images show robustness to low-quality image and better performance than conventional segmentation methods.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.73-81
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• 2018

The quality of side scan sonar images is determined by the frequency of a sonar. A side scan sonar with a low frequency creates low-quality images. One of the factors that lead to low quality is a high-level noise. The noise is occurred by the underwater environment such as equipment noise, signal interference and so on. In addition, in order to compensate for the transmission loss of sonar signals, the received signal is recovered by TVG (Time-Varied Gain), and consequently the side scan sonar images contain non-homogeneous noise which is opposite to optic images whose noise is assumed as homogeneous noise. In this paper, the SSCS (Structural Sparsity based Compressive Sensing) is proposed for removing non-homogeneous noise. The algorithm incorporates both local and non-local models in a structural feature domain so that it guarantees the sparsity and enhances the property of non-local self-similarity. Moreover, the non-local model is corrected in consideration of non-homogeneity of noises. Various experimental results show that the proposed algorithm is superior to existing method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4475-4481
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• 2014

A histogram equalization method have been used traditionally for the image enhancement of low quality images. This uses the transformation function, which is a cumulative density function of an input image, and it has mathematically maximum entropy. This method, however, may yield whitening artifacts. This paper proposes the weighted histogram equalization method based on histogram equalization. It has Weber-Fechner's law for a human's vision characteristics, and a dynamic range modification to solve the problem of some methods, which yield a transformation function, regardless of the input image. Finally, the proposed transformation function was calculated using the weighted average of Weber-Fechner and the histogram equalization transformation functions in a modified dynamic range. The simulation results showed that the proposed algorithm effectively enhances the contrast in terms of the subjective quality. In addition, the proposed method has similar or higher entropy than the other conventional approaches.