• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.1-12
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• 2005

Image registration is a process to establish the spatial correspondence between images of the same scene, which are acquired at different view points, at different times, or by different sensors. This paper presents a new algorithm for robust registration of the images acquired by multiple sensors having different modalities; the EO (electro-optic) and IR(infrared) ones in the paper. The two feature-based and intensity-based approaches are usually possible for image registration. In the former selection of accurate common features is crucial for high performance, but features in the EO image are often not the same as those in the R image. Hence, this approach is inadequate to register the E0/IR images. In the latter normalized mutual Information (nHr) has been widely used as a similarity measure due to its high accuracy and robustness, and NMI-based image registration methods assume that statistical correlation between two images should be global. Unfortunately, since we find out that EO and IR images don't often satisfy this assumption, registration accuracy is not high enough to apply to some applications. In this paper, we propose a two-stage NMI-based registration method based on the analysis of statistical correlation between E0/1R images. In the first stage, for robust registration, we propose two preprocessing schemes: extraction of statistically correlated regions (ESCR) and enhancement of statistical correlation by filtering (ESCF). For each image, ESCR automatically extracts the regions that are highly correlated to the corresponding regions in the other image. And ESCF adaptively filters out each image to enhance statistical correlation between them. In the second stage, two output images are registered by using NMI-based algorithm. The proposed method provides prospective results for various E0/1R sensor image pairs in terms of accuracy, robustness, and speed.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.132-142
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• 2014

Stereo camera is drawing attention as an essential sensor for future intelligence robot system since it has the advantage of acquiring not only distance but also other additive information for an object. However, it cannot match correlated point on target image for low textured region or periodic patterned region such as wall of building or room. In this paper, we propose a stereo matching technique that increase the matching performance by fusing belief propagation stereo matching algorithm and local distance measurements of 2D-laser range finder in order to overcome this kind of limitation. The proposed technique adds laser measurements by referring quad-tree based segment information on to the local-evidence of belief propagation stereo matching algorithm, and calculates compatibility function by reflecting over-segmented information. Experimental results of the proposed method using simulation and real test images show that the distance information for some low textured region can be acquired and the discontinuity of depth information is preserved by using segmentation information.

• Annual Conference of KIPS
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• 2024.05a
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• pp.108-111
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• 2024

클라우드 사용이 보편화 되고 확대됨에 따라, 서비스를 유연하게 확장 및 축소하여 신속하게 시장의 수요에 대응할 수 있는 PaaS(Platform-as-a-Service) 형태의 서비스가 많은 기업에서 각광받고 있다. 그리고 이러한 PaaS 형 서비스의 핵심이 되는 기술인 컨테이너(Container)와 컨테이너 관리를 효율화 해주는 쿠버네티스(Kubernetes)가 실질적인 표준으로 사용되고 있다. 이때 쿠버네티스 기반의 환경에서 서비스 어플리케이션은 다양한 구성사례가 존재하나, DB 는 아직 안정성 및 데이터 정합성 등을 이유로 베어메탈(Baremetal)이나 VM(Virtual Machine)을 기반으로 구성하고 있는 상황이다. 그러나, 인프라 구성 및 운영에 있어서도 파드(Pod) 형태의 DB 구성은 베어메탈 및 VM 대비 장점이 존재한다고 생각하여 본 실험을 수행하였다. 본 논문에서는 서비스 응답시간 및 자원 사용의 효율성 측면에서 VM 기반의 DB 와 쿠버네티스 파드 기반의 DB 에 각각 트래픽을 발생시켜서 비교한 결과와 시사점을 제시한다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.359-361
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• 2012

본 논문은 T2강조 MR 영상과 확산강조 MR 영상의 강체 정합을 통해 크기, 위치, 회전 변환 왜곡을 보정하여 자궁내막암의 위치를 자동으로 찾는 방법을 제안한다. 영상해상도와 밝기값 분포가 서로 다른 두 영상간 정합의 정확성을 향상시키기 위해 잡음을 제거하고 두 영상의 밝기값 신호 분포의 유사성을 강화시킨다. 유사성이 향상된 두 영상의 크기, 위치, 회전 변환 왜곡을 보정하기 위해 정규화 상호정보를 최대화 하는 강체 정합을 반복적으로 수행한다. 정합된 영상에서 악성 종양을 쉽게 판별 할 수 있도록 현상확상계수지도를 컬러맵으로 생성하여 T2강조 MR 영상에서 얻은 종양의 후보군에 매핑하여 T2강조 MR 영상과 융합한다. 실험을 위하여 최적화 반복 과정에 따른 정규화 상호정보 수치 수렴 과정을 확인하고, 융합 후 종양 영역이 매핑되는 것을 육안평가를 통해 분석하였다. 제안방법을 통하여 T2강조 MR 영상과 확산강조 MR 영상을 융합함으로써 종양의 위치를 자동으로 파악하고 자궁내막암의 병기를 확정하는 용도로 활용할 수 있다.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.59-66
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• 2004

In this paper, a fast 3D model extraction algorithm with an enhanced PBIL of preserving depth consistency is proposed for the extraction of 3D depth information from 2D images. Evolutionary computation algorithms are efficient search methods based on natural selection and population genetics. 2D disparity maps acquired by conventional matching algorithms do not match well with the original image profile in disparity edge regions because of the loss of fine and precise information in the regions. Therefore, in order to decrease the imprecision of disparity values and increase the quality of matching, a compact genetic algorithm is adapted for matching environments, and the adaptive window, which is controlled by the complexity of neighbor disparities in an abrupt disparity point is used. As the result, the proposed algorithm showed more correct and precise disparities were obtained than those by conventional matching methods with relaxation scheme.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.77-85
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• 2006

There is the spatial correlation of the video sequence between the motion vector of current blocks. In this paper, we propose the enhanced fast block matching algorithm using the spatial correlation of the video sequence and the center-biased properly of motion vectors. The proposed algorithm determines an exact motion vector using the predicted motion vector from the adjacent macro blocks of the current frame and the Cross-Hexagonal search pattern. From the of experimental results, we can see that our proposed algorithm outperforms both the prediction search algorithm (NNS) and the fast block matching algorithm (CHS) in terms of the search speed and the coded video's quality. Using our algorithm, we can improve the search speed by up to $0.1{\sim}38%$ and also diminish the PSNR (Peak Signal Noise Ratio) by at nst $0.05{\sim}2.5dB$, thereby improving the video qualify.

• Journal of the Korea Computer Industry Society
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• v.2 no.8
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• pp.1117-1122
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• 2001

Recently, issues on the internet searching of image information through various multimedia databases have drawn an tremendous attention and several researches on image information retrieval methods are on progress. By incorporating wavelet transform and correlation matrixes, we propose a novel and highly efficient feature vector extraction algorithm that has an capability of a robust similarity matching. The simulation results have yielded a faster and highly accurate candidate image retrieval performance in comparison to those of the conventional algorithms. Such an improved performance can be obtained because the used feature vectors were compressed to 256：1 while the correlation matrixes are incorporated to provide a fuel information for the better matching.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.767-774
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• 2002

Conventional research on image restoration has focused on restoring degraded images resulting from image formation, storage and communication, mainly in the signal processing field. Related research on recovering original image information of caption regions includes a method using BMA(block matching algorithm). The method has problem with frequent incorrect matching and propagating the errors by incorrect matching. Moreover, it is impossible to recover the frames between two scene changes when scene changes occur more than twice. In this paper, we propose a method for recovering original images using EBMA(Extended Block Matching Algorithm) and a region compensation method. To use it in original image recovery, the method extracts a priori knowledge such as information about scene changes, camera motion and caption regions. The method decides the direction of recovery using the extracted caption information(the start and end frames of a caption) and scene change information. According to the direction of recovery, the recovery is performed in units of character components using EBMA and the region compensation method. Experimental results show that EBMA results in good recovery regardless of the speed of moving object and complexity of background in video. The region compensation method recovered original images successfully, when there is no information about the original image to refer to.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.393-396
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• 2001

영상 압축 분야에서는 데이터 압축이 필수적인데, 이때 가장 많은 데이터 중복성을 가지고 있는 시간적 중복성은 이전 프레임의 데이터를 이용하여 움직임 추정과 움직임 보상을 수행하고 추정된 움직임 벡터에 의해서 보상된 영상과 원 영상과의 차 신호를 부호화하여 데이터를 압축한다. 움직임 추정과 움직임 보상기법은 비디오 영상압축에서 중요한 역할을 하지만 많은 계산량으로 인하여 실시간 응용이나 고해상도 응용에 많은 어려움을 가지고 있다. 이러한 문제점을 해결하기 위하여 여러 가지 고속정합 알고리즘들과 하드웨어 기법들이 개발되었다. 특히 다이아몬드 탐색 기법은 계산량도 줄이고 안정된 복원 영상 화질을 유지하고 있다. 본 논문에서는 기존의 다이아몬드 탐색 기법의 문제점을 개선한 수정된 다이아몬드 탐색 기법을 제안하고 성능을 평가한다. 실험에 의하여 제안된 기법은 기존의 다이아몬드 탐색 기법과 비교하여 화질 면에서나 속도 면에서 모두 좋은 결과를 가져왔다.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.