• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.763-766
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• 2002

오늘날 CT나 MR 등을 통한 의학 영상 기술과 컴퓨터 성능의 향상으로 인체 내부 장기의 영상을 비교적 용이하게 얻을 수 있으며 얻어진 영상 정보는 컴퓨터로 수치화되므로 데이터의 조작 및 가공 또한 용이하다. 그러나, 이 데이터는 2D 슬라이스(slice)들의 연속으로 표현되므로 이것을 보다 가시화, 조작, 분석이 용이한 상태로 바꾸기 위해서는 3 차원 구조로의 재구성이 필요하게 된다. 이것을 위하여 무엇보다도 먼저 CT 나 MR 을 통하여 얻어진 영상을 분석하여 특정장기(organ)의 영상 부분을 다른 조직의 영상부분으로부터 분리(segmentation)할 필요가 있다. 이러한 Segmentation방법에는 여러가지가 있는데, 수작업의 결합 등으로 인해서 비효율적일 수 밖에 없는 문제점을 가지고 있다. 이에 본 논문은 보다 효율적인 segmentation 의 처리를 위하여 구역확장(region-growing) 기법을 응용한 새로운 segmentation 방법을 개발하였다. 그리하여, 본 논문이 제안한 알고리즘을 슬라이스 간격이 큰 2 차원 복부 CT 영상에 적용시켜 간(liver)의 추출을 시도하였고 3차원 표현 결과를 확인할 수 있었다.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.1
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• pp.10-18
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• 2007

Mobile communication devices such as PDAs, cellular phones, etc., need to perform several kinds of computation-intensive functions including H.264 encoding/decoding and 3D graphics processing. In this paper, new reconfigurable architecture is described, which can perform either motion estimation for H.264 or rendering for 3D graphics. The proposed motion estimation techniques use new efficient SAD computation ordering, DAU, and FDVS algorithms. The new approach can reduce the computation by 70% on the average than that of JM 8.2, without affecting the quality. In 3D rendering, midline traversal algorithm is used for parallel processing to increase throughput. Memories are partitioned into 8 blocks so that 2.4Mbits (47%) of memory is shared and selective power shutdown is possible during motion estimation and 3D graphics rendering. Processing elements are also shared to further reduce the chip area by 7%.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.1
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• pp.23-30
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• 1980

The reconstruction problem in a low dose case requires some compromise of resolution and noise artifacts, and also some modification of filter kernels depending on the signal-to-noise ratio of projection data. In this paper, ail algorithm for the reconstruction of an image function from noisy projection data is suggested, based on minimum-mean-square error criterion. Modification of the falter kernel is made from information (statistics) obtained from the projection data. The simulation study Proves that this algorithm, based on the Wiener falter approach, provides substantially improved image with reduction of noise as well as improvement of the resolution. An approximate method was also studied which leads to the possible use of a recursive filter in the convolution process of image reconstruction.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.1-6
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• 2016

In this paper, we propose an image enhancement method for vehicle recorder by dividing the images into sub-images and finding local histograms of the sub-images. The proposed method includes the following steps. Firstly, the input image is divided into ($N{\times}M$) pieces. And the sub-images are used to make groups using the adjacent piece-images (eg. piece-imagei,j, piece-imagei,j+1, piece-imagei+1,j and piece-imagei+1,j+1). Secondly, the contrast enhancement processes are executed using the local histogram of the sub-images. Finally, overall image is reconstructed by using a transfer function that reflects the characteristics of the sub-image. The proposed method might achieve more enhanced images for vehicle recorder by suppressing excessive image contrast.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.676-680
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• 2001

본 논문에서는 2선식 양방향 통신이 가능한 I2C 제어기법을 이용하여 CCD 카메라와 Video 카메라로부터 아날로그 형태의 영상신호를 입력받아 다양한 포맷으로 디지털 영상을 지원하는 비디오 디코더를 설계하였고, 디지털화된 영상신호를 입력받아 NTSC와 S-VIDEO 방식으로 아날로그 영상신호를 재구성하는 stand-alone 시스템을 이용하여 비디오 엔코더를 설계하였다. 설계된 비디오 디코더와 엔코더를 이용하여 영상신호를 전송한 결과, EIA 포맷과 CCIR-xxx 포맷을 효율적으로 제어할 수 있음을 확인하였다.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.436-442
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• 2009

Tomography images reconstructed from conebeam CT make it possible to observe inside of the projected object without any damage, and so it has been widely used in the industrial and medical fields. Recent advanced imaging equipment can produce high-resolution CT images. However, it takes much time to reconstruct the obtained large dataset. To reduce the time to reconstruct CT images, we propose an accelerating method using GPU (graphics processing unit). Reconstruction consists of mainly two parts, filtering and back-projection. In filtering phase, we applied 4ch image compression method and in back-projection phase, computation reduction method using depth test is applied. The experimental results show that the proposed method accelerates the speed 50 times than the CPU-based program optimized with OpenMP by utilizing the high-computing power of parallelized GPU.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.70-71
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• 2010

요즘 감시카메라 시장은 전 세계적으로 이슈가 되고 있다. 감시카메라는 적은 인원으로 많은 장소를 한 눈에 감시할 수 있고, 문제가 발생했을 때, 녹화 저장된 영상을 통해 그 상황을 다시 볼 수 있다. 이렇게 다양한 기능과 편리함으로 우리에게 도움을 주는 감시카메라이지만, 마스크나 선글라스, 또는 여러 가지 잡음에 의해 얼굴 영상의 부분이 훼손되는 상황에서는 신원 확인을 하기가 어렵다. 때문에 가려진 얼굴을 제대로 인식하기 위해 영상 처리 분야에서 얼굴의 가려진 영역을 찾아 그 부분을 재구성하고자 하는 연구가 활발히 진행되고 있다. 이에 본 논문은 기존 PCA 방법을 이용하여 가려진 영역을 찾아내고, PCA를 반복적으로 사용하여 재구성하는 대신 상관관계를 이용하여 얼굴의 가려진 영역을 자동적으로 검출하고 복원하는 방법을 제안한다. 본 논문에서는 두 눈의 중심이 고정되어 있는 BioID 데이터로 상관계수를 구하고 얼굴의 특정 부분을 임의로 가려 실험을 수행하였다. 제안된 방법의 결과는 PCA 방법으로 수행한 결과와 함께 비교되어 원본 영상과의 오류 값이 더 작게 나오는 것을 확인할 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.169-178
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• 2001

The demand for high-resolution images is gradually increasing, whereas many imaging systems have been designed to allow a certain level of aliasing during image acquisition. Thus, digital image processing approaches have recently been investigated to reconstruct a high-resolution image from aliased low-resolution images. However, since the sub-pixel motion information is assumed to be accurate in most conventional approaches, the satisfactory high-resolution image cannot be obtained when the sub-pixel motion information is inaccurate. Therefore, in this paper we propose a new algorithm to reduce the distortion in the reconstructed high-resolution image due to the inaccuracy of sub-pixel motion information. For this purpose, we analyze the effect of inaccurate sub-pixel motion information on a high-resolution image reconstruction, and model it as zero-mean additive Gaussian errors added respectively to each low-resolution image. To reduce the distortion we apply the modified multi-channel image deconvolution approach to the problem. The validity of the proposed algorithm is both theoretically and experimentally demonstrated in this paper.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3703-3709
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• 1999

We propose a new approach to reconstruct the surface shape of an object from a shaded image. We use genetic algorithm instead of gradient descent algorithm which is apt to take to local minima and also proposes genetic representation and suitable genetic operators for manipulating 2-D image. And for more effective execution, we suggest hierarchical process to reconstruct minutely the surface of an object after coarse and global reconstruction. A modified Lambertian illumination model including the distance factor was herein adopted to get more reasonable result and an experiment was performed with synthesized and real images to demonstrate the devised method, of which results show the usefulness of our method.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2027-2040
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• 1998

In this paper, we present efficient reconfigurable mesh algorithms for transforming between a binary image and its corresponding boundary code. These algorithms use $n\timesn\timesn$ processors when the size of the binary image is $n\timesn$. Recent published results show that these transformations can be done in O(1) time using $O(n^4)$ processors. The number of processors used by these algorithms is very large compared to the number of pixels in the image. Here, we present fast transformation algorithms which use $n^3 processors only. the transformation from a houndary code to a binary image takes O(1) time, and the converse transformation takes O(log n) time.