• Journal of Broadcast Engineering
• /
• v.25 no.5
• /
• pp.685-697
• /
• 2020

Immersive media videos, such as panorama and 360-degree videos, must provide a sense of realism as if the user visited the space in the video, so they should be able to represent the reality of the real world. However, in panorama and 360-degree videos, objects appear to overlap or disappear due to parallax between cameras, and such parallax distortion may interfere with immersion of the user's content. Accordingly, although many video stitching algorithms have been proposed to overcome parallax distortion, parallax distortion still occurs due to the low performance of the Object detection module and limitations of the Seam generation method. Therefore, this paper analyzes the limitations of the existing video stitching technology and proposes a method for detecting and correcting parallax distortion of video stitching using the LDPM (Local Differential Pixel Mean) image evaluation method that overcomes the limitations of the video stitching technique.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.8 no.3
• /
• pp.105-112
• /
• 1983

This paper discribes technique of the recursive restoration for the images degraded by linear space invariant blur and additive white Gaussian noise. The image is characterized statistically by tis mean and correlation function. An exponential autocorrelation function has been used to model neighborhood model. The vector model was used because of analytical simplicitly and capability to implement brightness correlation function. Base on the vector model, a two-dimensional discrete stochastic a 12 point neighborhood model for represeting images was developme and used the technique of moving window processing to restore blurred and noisy images without dimensionality increesing, It has been shown a 12 point neighborhood model was found to be more adequate than a 8 point pixel model to obtain optimum pixel estimated. If the image is highly correlated, it is necessary to use a large number of points in the neighborhood in order to have improvements in restoring image. It is believed that these result could be applied to a wide range of image processing problem. Because image processing thchniques normally required a 2-D linear filtering.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.141-143
• /
• 2010

This paper presents a problem of the existing encryption method using MLCA or complemented MLCA and propose a method to resolve this problem. With the existing encryption methods, the result of encryption is affected by the original image because of spatial redundancy of adjacent pixels. In this proposed method, we transform spatial coordinates of all pixels into encrypted coordinates. We also encrypt color values of the original image by operating XOR with pseudo-random numbers. This can solve the problem of existing methods and improve the levels of encryption by randomly encrypting pixel coordinates and pixel values of original image. The effectiveness of the proposed method is proved by conducting histogram, key space analysis.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.1
• /
• pp.190-196
• /
• 2013

Curved integral imaging is a simple method to display 3D images in space using lens array and provides wide viewing angle. In this paper, we propose a nonlinear 3D correlator based on the direct pixel-mapping (DPM) method in order to improve the recognition performance of 3D target object in curving-effective integral imaging. With this scheme, the elemental image array (EIA) originally picked up from a partially occluded 3-D target object can be converted into a resolution enhanced new EIA by using DPM method. Then, through nonlinear cross-correlations between the reconstructed reference and the target plane images, the improved pattern recognition can be performed from the correlation outputs. To show the feasibility of the proposed method, some preliminary experiments are carried out and results are presented by comparing the conventional method.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.7 no.2
• /
• pp.16-28
• /
• 2004

A seam-line determination algorithm is proposed to determine image border-line in mosaicing using the transformation of gray value differences and dynamic programming. Since visually good border-line is the one along which pixel differences are as small as possible, it can be determined in association with an optimal path finding algorithm. A well-known effective optimal path finding algorithm is the Dynamic Programming (DP). Direct application of the dynamic programming to the seam-line determination causes the distance effect, in which seam-line is affected by its length as well as the gray value difference. In this paper, an adaptive cost transform algorithm with which the distance effect is suppressed is proposed in order to utilize the dynamic programming on the transformed pixel difference space. Also, a figure of merit which is the summation of fixed number of the biggest pixel difference on the seam-line (SFBPD) is suggested as an evaluation measure of seamlines. The performance of the proposed algorithm has been tested in both quantitively and visually on various kinds of images.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.1
• /
• pp.58-63
• /
• 2020

This paper proposes the method for improving the localization accuracy of the mobile robot based on the stereo camera. To restore the position information from stereo images obtained by the stereo camera, the corresponding point which corresponds to one pixel on the left image should be found on the right image. For this, there is the general method to search for corresponding point by calculating the similarity of pixel with pixels on the epipolar line. However, there are some disadvantages because all pixels on the epipolar line should be calculated and the similarity is calculated by only pixel value like RGB color space. To make up for this weak point, this paper implements the method to search for the corresponding point simply by calculating the gap of x-coordinate when the feature points, which are extracted by feature extraction and matched by feature matching method, are a pair and located on the same y-coordinate on the left/right image. In addition, the proposed method tries to preserve the number of feature points as much as possible by finding the corresponding points through the conventional algorithm in case of unmatched features. Because the number of the feature points has effect on the accuracy of the localization. The position of the mobile robot is compensated based on 3-D coordinates of the features which are restored by the feature points and corresponding points. As experimental results, by the proposed method, the number of the feature points are increased for compensating the position and the position of the mobile robot can be compensated more than only feature extraction.

• Tunnel and Underground Space
• /
• v.29 no.3
• /
• pp.184-196
• /
• 2019

This study aims to extract a 3D image of micro-cracks generated by hydraulic fracturing tests, using the deep learning method and X-ray computed tomography images. The pixel-level cracks are difficult to be detected via conventional image processing methods, such as global thresholding, canny edge detection, and the region growing method. Thus, the convolutional neural network-based encoder-decoder network is adapted to extract and analyze the micro-crack quantitatively. The number of training data can be acquired by dividing, rotating, and flipping images and the optimum combination for the image augmentation method is verified. Application of the optimal image augmentation method shows enhanced performance for not only the validation dataset but also the test dataset. In addition, the influence of the original number of training data to the performance of the deep learning-based neural network is confirmed, and it leads to succeed the pixel-level crack detection.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.3
• /
• pp.240-245
• /
• 2013

Each pixel of InfraRed(IR) sensor differently responds to IR light as time elapses or the sensor on/off operation is repeated. As a result, the quality of IR sensor image is deteriorated, and therefore NUC(Non-uniformity Correction) is periodically needed for IR sensor. In this paper, in order to perform NUC in the Satellite, on-board V-grooved blackbody is designed with a baffle so that the emissivity of black body is to be higher than 0.995 as well as the temperature deviation is less than $1^{\circ}C$ in the range of the infrared wave length from 3.3 to $5.2{\mu}m$. To check its performance, the emissivity and the surface temperature of the blackbody by TRT(Transfer Reference Thermometer) and IR Micrometer scanner are measured, respectively. From the results, black body design is verified and the uncertainty of NUC is estimated through the measurement results.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10b
• /
• pp.826-831
• /
• 1988

This paper presents an approach to segment an image into areas of surfaces, and to compute the surface properties from a gray-scale image in order to describe the surfaces for reconstruction of the 3-D shape of the objects. In general, an rigid body has several surfaces and many edges. But if it is not polyhedoron, it is necessary not only to describe the relation between surfaces, i.e. its line drawings but also to represent the surfaces' equations itself. In order to compute the surfaces' equation we use a probability of edge distribution. At first it is extracted edges from a gray-level image as much as possible. These are not only the points that maximize the change of an image intensuty but candidates which can be seemed to be edges. Next, other character of a surface (color, coordinates and image intensity) are extracted. In our study, we call the all feature of a surface as "texture", for example color, intensity level, orientation of an edge, shape of a surface and so on. These features of a surface on a pixel of an image plane are mapped to a point of the feature space, and segmented to each groups by cluster analysis on this space. These groups are considered to represent object surface in an image plane. Finally, the states of object surface in 3-D space are computed from distributional probability of local and overall statistical features of a surface, and from shape of a surface.a surface.

• Bulletin of the Korean Space Science Society
• /
• 2009.10a
• /
• pp.45.1-45.1
• /
• 2009

과학기술위성 3호의 주탑재체인 MIRIS (Multi-purpose InfraRed Imaging System)는 우주관측카메라 (Space Observation Camera, SOC)와 지구관측카메라 (Earth Observation Camera, EOC)가 독립적인 시스템으로 구성되어 있다. 지구관측카메라는 유효 구경 100 mm, F/5의 광학계로 3-5 마이크론 파장영역을 관측하며, 국내에서 개발된 적외선 검출기의 우주 인증 시험과 유사시 한반도 적외선 감시를 주요 목적으로 하고 있다. 고도 700km에서 지상을 볼 때 약 42m/pixel의 공간분해능을 나타낼 것으로 기대하고 있다. 지구관측카메라의 인증 모델(Qualification Model)은 냉동기를 제외한 모든 부품이 국내기술로 제작되었으며, 미러 본딩 및 릴레이 렌즈 조립 기술, 적외선 영상 검교정 기술 등 다양한 경험과 도전을 제공했다. 이 발표에서는 지구관측카메라 인증모델을 이용하여 수행한 주요 시험 과정을 소개한다. 국내 회사 (주)i3 system에서 제작된 적외선 검출기는 $320\times256$ HgCdTe array (평균 양자효율 80% 이상) 이며 77K에서 정상적으로 운영된다. Micro Stirling Cooler에 의해 듀어는 전원을 켠 후 5분 이내에 검출기 운영온도인 77K까지 내려간다. 적외선 광학계의 정렬, 시스템 MTF 측정, 흑체 측정 및 검교정 작업을 수행한 후 야외에서 다양한 경우에 대해 Field Test를 진행했다. 이 발표에서는 Field Test 과정과 이를 통해 얻은 결과를 발표하고, FM (Flight Model) 제작에 있어 수정해야 할 사항들을 제안해 본다.