• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.104-107
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• 2018

최근 촬영 기기의 기술발전으로 인해 디지털 영상의 해상도가 증가함에 따라 선명한 디지털 영상에 대한 요구가 증가하고 있다. 이러한 요구에도 불구하고 디지털 영상 내 가우시안 잡음 (gaussian noise)은 촬영기기를 통해 영상 획득 및 처리 과정에서 발생하여 화질을 열화 시킨다. 디지털 이미지에서 발생하는 가우시안 잡음을 제거하기 위해서 기존의 저대역 통과 필터 (low-pass filter: LPF)를 사용하면 잡음은 제거되지만, 블러링 현상 (blurring phenomenon)이 나타난다. 이러한 문제점을 개선하기 위해 소벨 연산자 (sobel operator)를 사용하여 영상 내 에지 맵 (edge-map)을 생성하여 에지 영역과 동질 영역을 구분한다. 에지영역에서는 약한 저역 필터 (weak low-pass filter)를 사용하고, 그 외의 이미지 영역에서는 강한 저역 필터 (strong low-pass filter)를 사용하는 알고리듬을 제안하였다. 그리고 다양한 이미지에 대하여 기존 알고리듬과 제안한 알고리듬의 적용한 결과를 통해 주관적 화질 비교하였고 객관적 지표로 최대 신호 대 잡음비 (peak signal-to noise ratio: PSNR)와 구조 유사성 (structural similarity: SSIM)을 사용하여 성능을 평가하였다. 실험결과를 통해 제안된 알고리듬이 잡음 제거 및 외곽선 보존의 우수함을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.19-26
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• 2006

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor (EHD) is time consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by the only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.27-34
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• 2011

In this paper, the novel approach for image contrast enhancement is introduced. The method is based on the unsharp mask and directional information of images. Since the unsharp mask techniques give better visual quality than the conventional sharpening mask, there are much works on image enhancement using unsharp masks. The proposed algorithm decomposes the image to several blocks and extracts directional information using DCT. From the geometric properties of the block, each block is labeled as appropriate type and processed by adaptive unsharp mask. The masking process is skipped at the flat area to reduce the noise artifact, but at the texture and edge area, the adaptive unsharp mask is applied to enhance the image contrast based on the edge direction. Experiments show that the proposed algorithm produces the contrast enhanced images with superior visual quality, suppressing the noise effects and enhancing edge at the same time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.717-724
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• 2016

This paper proposes a change detection method based on the covariance matrices of color and edge gradient in a color video. The YCbCr color format was used instead of RGB. The color covariance matrix was calculated from the CbCr-channels and the edge gradient covariance matrix was calculated from the Y-channels. The covariance matrices were effectively calculated at each pixel by calculating the sum, squared sum, and sum of two values' multiplication of a rectangle area using the integral images from a background image. The background image was updated by a running the average between the background image and a current frame. The change areas in a current frame image against the background were detected using the Mahalanobis distance, which is a measure of the statistical distance using covariance matrices. The experimental results of an expressway color video showed that the proposed approach can effectively detect change regions for color and edge gradients against the background.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.57-66
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• 2011

In this paper, it is proposed for algorithm to detect human efficiently using a edge symmetry and gradient directional characteristics in realtime by the feature extraction in a single input image. Proposed algorithm is composed of three stages, preprocessing, region partition of human candidates, verification of candidate regions. Here, preprocessing stage is strong the image regardless of the intensity and brightness of surrounding environment, also detects a contour with characteristics of human as considering the shape features size and the condition of human for characteristic of human. And stage for region partition of human candidates has separated the region with edge symmetry for human and size in the detected contour, also divided 1st candidates region with applying the adaboost algorithm. Finally, the candidate region verification stage makes excellent the performance for the false detection by verifying the candidate region using feature vector of a gradient for divided local area and classifier. The results of the simulations, which is applying the proposed algorithm, the processing speed of the proposed algorithms is improved approximately 1.7 times, also, the FNR(False Negative Rate) is confirmed to be better 3% than the conventional algorithm which is a single structure algorithm.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.155-163
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• 1999

In this paper, we propose novel scene change detection and key frame selection techniques, which use two feature images, i.e., DC and edge images, extracted directly from MPEG compressed video. For fast edge image extraction. we suggest to utilize 5 lower AC coefficients of each DCT. Based on this scheme, we present another edge image extraction technique using AC prediction. Although the former is superior to the latter in terms of visual quality, both methods all can extract important edge features well. Simulation results indicate that scene changes such as cut. fades, and dissolves can be correctly detected by using the edge energy diagram obtained from edge images and histograms from DC images. In addition. we find that our edge images are comparable to those obtained in the spatial domain while keeping much lower computational cost. And based on HVS, a key frame of each scene can also be selected. In comparison with an existing method using optical flow. our scheme can select semantic key frames because we only use the above edge and DC images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2982-2988
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• 2014

The edge detection is a pre-processing of such as image segmentation, image recognition, etc, and many related studies are being conducted both in domestic and abroad. Representative edge detection methods are Sobel, Prewitt, Laplacian, Roberts and Canny edge detectors. Such existing methods are possible for superb detections of edges if edges are detected from videos without noises. However, for video degraded by the salt-and-pepper noise, the edge detection characteristic is shown to be insufficient due to the noise influence. Therefore, in this study, the area is separated as the top, down, left and right from the mask's center pixel first to acquire a superb edge detection characteristic from the video damaged by the salt-and-pepper noise. And the algorithm that detects the final edge by applying the directional mask on the assumed factor of mask that is obtained according to the result of determination for the noise status of representative pixel value of each area.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.12
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• pp.640-647
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• 2002

In this paper, we consider the problems related to the edge visibility on a reconfigurable mesh(in short, RMESH). The following basic problems related to the edge visibility are considered: First, determine if a given polygon is visible from a specific edge, Second, find all edges from which a given polygon is visible. Third, compute the visibility polygon from a specific edge of a given polygon. In this paper, we consider the following problem in order to solve these problems in constant time: given two edges e and f of a simple polygon p, compute the maximal interval of f which is visible from e. We present a constant time algorithm for the problem on an N-N RMESH, where N is the number of vertices of P. Applying the algorithm, we can solve the above three problems in a constant time on a reconfigurable mesh. Specially, we can solve the third problem in a constant time on an N-$N_2$ RMESH.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.137-144
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• 2005

In this paper, the extraction method of the edge histogram directly using wavelet coefficients in the wavelet domain for JPEG2000 images is proposed. MPEG-7 Edge Histogram Descriptor(EHD) extracts edge histogram in the spacial domain. This algorithm has much multiplication and addition for the edge extraction because it needs the decoding processing. However because the proposed algorithm extracts the edge histogram in the wavelet domain, it doesn't need the decoding processing and it decreases multiplication and addition. The Discrete Wavelet Transform(DWT) is a standard transform in JPEG2000. The proposed algorithm uses Le Gall 5/3 filter in JPEG2000 and odd coefficients in LH2 and HL2 sub-band. The edge direction can be decided to use rate of HL2 and LH2 odd coefficients. According to experiments, there is no difference of the efficiency between EHD and the proposed algorithm And the proposed algorithm is much better than EHD for multiplication and addition in the edge extraction of images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.360-362
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• 2018

본 논문에서는 X-ray 영상에서 척추 영역을 추출 및 분석하여 척추만곡도를 자동으로 측정하는 방법을 제안한다. 제안된 방법은 X-ray 영상에서 어깨뼈와 골반뼈 등과 같이 필요 없는 영역을 제거한 ROI(Region of Interest) 영역을 추출하고, 추출된 ROI 영역에서 척추 에지를 검출하기 위해 가우시안-라플라시안(Laplacian of Gaussian) 필터를 적용하여 척추 에지를 검출한다. 추출된 척추 영역을 척추의 Apex를 기준으로 Above Apex와 Below Apex 영역으로 구분하고 허프 변환(Hough Transform) 기법을 적용하여 두 영역에 대한 ($r,{\theta}$) 허프 공간을 구한다. ($r,{\theta}$) 허프 공간에서 척추만곡도 측정에 필요한 수평 직선만을 검출하기 위하여 수직 직선을 나타내는 교점들의 영역을 제거하여 척추만곡도 측정에 필요한 영역을 추출한다. 제안된 척추 추출 방법을 다양한 X-ray 영상을 대상으로 실험한 결과, 전문의가 척추만곡도를 효과적으로 측정하고 분석할 수 있는 척추 영역이 추출된 것을 확인할 수 있었다.