• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2017.06a
• /
• pp.149-150
• /
• 2017

본 논문에서는 RGB-stripe 부화소 구조를 갖는 디스플레이에서 인지 화질을 향상시키면서, 색 왜곡을 저감할 수 있는 부화소 렌더링을 수행한다. 우선 인지 화질을 향상 시키는 주 필터와, 색 왜곡을 억제하는 비음수 필터를 디자인한다. 색 왜곡 가능성의 계산에 따라, 두 필터를 조합하고 영상을 렌더링 한다. 실험 결과, 본 논문의 부화소 렌더링 방법이 비교 방법에 비해 좋은 인지 화질을 얻으면서도 색 왜곡을 억제함을 보여준다.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.6
• /
• pp.1183-1189
• /
• 2011

In this study, we propose the unsupervised image segmentation algorithm to estimate dental plaque accumulations on digital imaging with methylene blue disclosed plaque. With this aim, RGB color plane is mapped into HSI coordinates and the circular histogram of Hue is reconstructed by applying Otsu's threshold level. The histogram distribution on Saturation features is also analyzed by maximizing the variance between a plaque candidate and non-plaque one. The dental plaque regions are resolved by applying the composite decision logics based on the threshold level of Hue and Saturation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.6
• /
• pp.1136-1142
• /
• 2010

In this study, an efficient removal algorithm for specular reflections in a tooth color image is proposed to minimize the artefact interrupting color image segmentation. The pixel values of RGB color channels are initially reversed to emphasize the features in reflective regions, and then those regions are automatically detected by utilizing perceptron artificial neural network model and those prominent intensities are corrected by applying a smoothing spatial filter. After correcting specular reflection regions, multiple seeds in the tooth candidates are selected to find the regional minima and MCWA(Marker-Controlled Watershed Algorithm) is applied to delineate the individual tooth region in a CCD tooth color image. Therefore, the accuracy in segmentation for separating tooth regions can be drastically improved with removing specular reflections due to the illumination effect.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1845_1846
• /
• 2009

본 논문에서는 특징 벡터를 이용한 강인한 물체 추적 방법을 제안한다. 먼저, 초기 이동 물체의 움직임 영역을 추출하고, KLT알고리즘을 입력 영상에 적용시켜 특징 벡터들을 추출한다. 초기 추출된 이동 물체의 움직임 영역에 추출된 특징 벡터를 적용시켜 1차 정규화 한다. 그 후, RGB 칼라모델과 HSI 칼라모델을 이용하여 이동 물체에 대한 Blob 영역을 설정하고 설정된 Blob 영역에 대해 1차 특징벡터를 Snake 알고리즘으로 동정하여 2차 정규화 과정을 마무리 한다. 최종 정규화 된 특징 벡터를 Particle filter에 입력 데이터로 이용하여 이동 물체를 추적 한다. 마지막으로, 복잡한 환경에서 실험을 통해 그 응용 가능성을 증명한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2000.10a
• /
• pp.522-527
• /
• 2000

본 논문은 그레이이미지를 컬러이미지로 변환하는 의사칼라이미지 향상에 관한 연구이다. 적용기법은 그레이이미지의 시간영역신호를 주파수영역으로 변환하고 LPF, BPF, HPF 2차원필터를 통과시켜 시간영역으로 역 변환한 후 각각에 대해 히스토그램 평활화하여 RGB 신호를 구하는 과정에서 의사 칼라를 얻는다. 실험 결과 필터주파수가 증가함에 따라 PSNR도 증가하고 낮게 설정하면 경계부분의 화질이 좋아진다. 2차원 주파수필터의 사용은 칼라 변환 시 강조하고자 하는 부분을 보다 자유롭게 변환할 수 있고 다양한 컬러 이미지로 향상되어 영상분석에 효과가 있다. 의사칼라의 변환에 의한 식별 인식능력은 9dB 정도 향상된다.

• The Transactions of the Korean Institute of Electrical Engineers C
• /
• v.51 no.1
• /
• pp.46-54
• /
• 2002

Plasma Display Panel (PDP) is required to be both the determination of white point of each gray level and the inverse gamma correction since no-balanced RGB cell and linear property of PDP, respectively. However, these two methods cause degradation of grey level representation and undesirable false contour in the dark areas on PDP. In this paper, we implemented real time image processor of the proposed error diffusion algorithm and unsharp masking operation to protect the blurring image caused by the error diffusion. Experimental results showed drastic improvements of gray level representation and reduction of undesirable false contour.

• Journal of Information Technology Applications and Management
• /
• v.9 no.3
• /
• pp.1-12
• /
• 2002

Due to the fast development in computer and communication technologies, a video is now being more widely used than ever in many areas. The current information analyzing systems are originally built to process text-based data. Thus, it has little bits problems when it needs to correctly represent the ambiguity of a video, when it has to process a large amount of comments, or when it lacks the objectivity that the jobs require. We would like to purpose an algorithm that is capable of analyze a large amount of video efficiently. In a video, divided areas use a region growing and region merging techniques. To sample the color, we translate the color from RGB to HSI and use the information that matches with the representative colors. To sample the shape information, we use improved moment invariants(IMI) so that we can solve many problems of histogram intersection caused by current IMI and Jain. Sampled information on characteristics of the streaming media will be used to find similar frames.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.9-11
• /
• 2005

We propose a new content-based image retrieval using a block color co-occurrence matrix (BCCM) and pattern correlogram. In the proposed method, the color feature vectors are extracted by using BCCM that represents the probability of the co-occurrence of two mean colors within blocks. Also the pattern feature vectors are extracted by using pattern correlogram which is combined with spatial correlation of pattern. In the proposed pattern correlogram method. after block-divided image is classified into 48 patterns with respect to the change of the RGB color of the image, joint probability between the same pattern from the surrounding blocks existing at the fixed distance and the center pattern is calculated. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.186-188
• /
• 2005

Hand region detection in images is an important process in many computer vision applications. It is a process that usually starts at a pixel-level, and that involves a pre-process of color space transformation followed by a classification process. A color space transformation is assumed to increase separability between skin classes for hands and non-skin classes for other parts, to increase similarity among different skin tones, and to bring a robust performance under varying illumination conditions, without any sound reasonings. In this work, we examine if the color space transformation does bring those benefits to the problem of hand region detection on a dataset of images with different hand postures, backgrounds, people, and illuminations. Results indicate that best of the color space is the normalized RGB.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.861-862
• /
• 2008

This paper presents the results of iris region localization for imprecisely taken iris images in UBIRIS ver2. UBIRIS database consisting of 500 images of 24-bit RGB typed TIFF file. They were captured by conventional digital camera in visible light environment. Experimental result showed that FP(False Positive rate) and FN(False Negative rate) were about 2.2% and 29.1%, respectively.