• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.4
• /
• pp.663-670
• /
• 2019

The modified Canny edge detection algorithm that can detect the boundary between screen door and platform in the subway is proposed in this paper. Generally, in the subway, the boundary line between the platform and the screen door is darker than the surrounding area. Therefore, an edge image is using the modified bottom-hat transform by considering its characteristics. Double thresholded images with strong edge and weak edge through double thresholding are obtained. An algorithm that detects the boundary invasion between the platform and the screen door is proposed by calculating the length by applying the Hough transform to the double thresholded image and comparing the boundary line length between when there is an object such as a person and when there is no object. In this paper, the results of the proposed modified Canny edge detection algorithm using two different input images according to camera height position are shown by computer simulation.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.5 s.305
• /
• pp.95-102
• /
• 2005

When images compressed with block-based compression techniques are transmitted over a noisy channel, unexpected block losses occur. In this paper, we present a post-processing-based block recovery scheme using Haar wavelet features. No consideration of the edge-direction, when recover the lost blocks, can cause block-blurring effects. The proposed directional recovery method in this paper is effective for the strong edge because exploit the varying neighboring blocks adaptively according to the edges and the directional information in the image. First, the adaptive selection of neighbor blocks is performed based on the energy of wavelet subbands (EWS) and difference of DC values (DDC). The lost blocks are recovered by the linear interpolation in the spatial domain using selected blocks. The method using only EWS performs well for horizontal and vertical edges, but not as well for diagonal edges. Conversely, only using DDC performs well diagonal edges with the exception of line- or roof-type edge profiles. Therefore, we combined EWS and DDC for better results. The proposed methods out performed the previous methods using fixed blocks.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.3
• /
• pp.260-265
• /
• 2015

This paper proposes a alignment system using edge feature. An alignment system obtains the position and orientation of printed circuit board(PCB) or liquid crystal display(LCD) panel through the fiducial marks. Thus, it is the indicator of the system performance how accurate we detect the positions of the fiducial marks in the target image. Edges have the geometrical characteristics such as positions, lengths, and shapes. These features are suitable for finding the marks and have the advantages of lighting variations, model occlusion, as well as variations in scale and angle. The performance of the proposed system is validated through the alignment experiment using an display panel alignment system included X, Y axis, and rotatable stage.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.5
• /
• pp.87-94
• /
• 2008

In this paper, we present a directional error concealment technique to compensate a lost block. Generally, the strong edge of an image has the large amounts of the variance because of its large coefficients in the wavelet domain. For estimating edge direction of a lost block, a $X^2$ hypothesis-testing problem is applied using the variance of wavelet coefficients. The lost block is interpolated according to the estimated edge direction. The pixels for interpolation is obtained from the edge direction. The proposed method outperforms the previous methods in objective and subjective qualities.

• The KIPS Transactions:PartB
• /
• v.14B no.3 s.113
• /
• pp.171-182
• /
• 2007

We propose a simple method for tracking a nonparameterized subject contour in a single video stream with a moving camera and changing background. Then we present a method to eliminate the tracked contour object by replacing with the background scene we get from other frame. First we track the object using LOD (Level-of-Detail) canny edge maps, then we generate background of each image frame and replace the tracked object in a scene by a background image from other frame that is not occluded by the tracked object. Our tracking method is based on level-of-detail (LOD) modified Canny edge maps and graph-based routing operations on the LOD maps. We get more edge pixels along LOD hierarchy. Our accurate tracking is based on reducing effects from irrelevant edges by selecting the stronger edge pixels, thereby relying on the current frame edge pixel as much as possible. The first frame background scene is determined by camera motion, camera movement between two image frames, and other background scenes are computed from the previous background scenes. The computed background scenes are used to eliminate the tracked object from the scene. In order to remove the tracked object, we generate approximated background for the first frame. Background images for subsequent frames are based on the first frame background or previous frame images. This approach is based on computing camera motion. Our experimental results show that our method works nice for moderate camera movement with small object shape changes.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.3
• /
• pp.46-54
• /
• 2008

Most commercial CCD/CMOS image sensors have CFA(Color Filter Array) where each pixel gathers light of a selective color to reduce the sensor size and cost. There are many algorithms proposed to reconstruct the original clolr image by adopting pettern recognition of regularization methods to name a few. However the resulting image still suffer from errors such as flase color, zipper effect. In this paper we propose an adaptive edge weight demosaicking algorithm that is based on POCS(Projection Onto Convex Sets) not only to improve the entire image's PSNR but also to reduce the edge region's errors that affect subjective image quality. As a result, the proposed algorithm reconstruct better quality images especially at the edge region.

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

• Proceedings of the Korea Multimedia Society Conference
• /
• 2000.11a
• /
• pp.262-265
• /
• 2000

영상에서의 경계선추출은 영상의 강도의 변화를 이용한 경계영역의 가시화 기법이므로 gray level 영상이 가지는 강도를 이용하여 에지를 찾을 수 있다. 뇌 영상에는 MRI 영상과 같이 해부학적인 정보가 큰 영상과, PET 영상같이 perfusion으로 분석해야 할 영상이 있는데 그 경계가 뚜렷한 MRI 영상과 달리 PET 뇌 영상은 영상의 특성상 경계영역의 구분이 모호한 실정이다. 본 논문에서는 이러한 영상의 특성에 따라 뇌 영상에서 영상 강도에 대해 등분할을 한 후 vectorgram에서 magnitude의 영역을 선택하여 영상을 분할 하였다. 그리고 PET 와 MRI영상과 현미경 영상에 대한 결과를 비교하였다. Vertcrgram은 에지정보를 가지는 영상에 대해 벡터요소를 그래프화 한 것으로 방향성에 대한 평가를 통해 영역 분할을 하였다. 이러한 PET 영상의 2차원 분할 방법은 3차원 PET 영상 분석에 응용될 수 있을 것이다.

• Journal of KIISE:Computer Systems and Theory
• /
• v.33 no.8
• /
• pp.536-546
• /
• 2006

Painterly animation is a method that expresses painterly images with a hand-painted appearance from a video, and the most crucial element for it is the temporal coherence of brush strokes between frames. A motion map is proposed in this paper as a solution to the issue of maintaining the temporal coherence in the brush strokes between the frames. A motion map is the region that frame-to-frame motions have occurred. Namely, this map refers to the region frame-to-frame edges move by the motion information with the motion occurred edges as a starting point. In this paper, we employ the optical flow method and block-based method to estimate the motion information. The method that yielded the biggest PSNR using the motion information (the directions and magnitudes) acquired by various methods of motion estimation has been chosen as the final motion information to form a motion map. The created motion map determine the part of the frame that should be re-painted. In order to express painterly images with a hand- painted appearance and maintain the temporal coherence of brush strokes, the motion information was applied to only the strong edges that determine the directions of the brush strokes. Also, this paper seek to reduce the flickering phenomenon between the frames by using the multiple exposure method and the difference map created by the difference between images of the source and the canvas. Maintenance of the coherence in the direction of the brush strokes was also attempted by a local gradient interpolation to maintain the structural coherence.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.9
• /
• pp.119-126
• /
• 2013

In this paper, we propose a chromatic aberration removal algorithm in image capture devices, which considers local properties of the image. Chromatic aberration is generated by the fact that the refractive index of the lens is different for different wavelengths, which produces color artifacts on strong edge due to misalignment of RGB channels. Under the characteristics of the artifacts, the proposed algorithm first estimates the regions with the apparent color artifacts as the neighborhoods of the strong edge. In the regions, the proposed algorithm removes the color artifacts by matching the edges of RGB channels. The widely used conventional methods based on global image warping could not remove the color artifacts of longitudinal chromatic aberration and purple fringing identified by the image sensor, whereas the matching process of the proposed method could reduce them. Experimental results show that the proposed algorithm outperforms the conventional methods on objective and subjective criteria.