• 한국융합학회논문지
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• 제5권3호
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• pp.41-44
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• 2014

Sequential object analysis are playing vital role in real time application in computer vision and object detections.Measuring the similarity in two images are very important issue any authentication activities with how best to compare two independent images. Identification of similarities of two or more sequential images is also the important in respect to moving of neighborhoods pixels. In our study we introduce the morphological and shared near neighborhoods concept which produces a sufficient results of comparing the two images with objects. Considering the each pixel compare with 8-connectivity pixels of second image. For consider the pixels we expect the noise removed images are to be considered, so we apply the morphological transformations such as opening, closing with erosion and dilations. RGB of pixel values are compared for the two sequential images if it is similar we include the pixels in the resultant image otherwise ignore the pixels. All un-similar pixels are identified and ignored which produces the similarity of two independent images. The results are produced from the images with objects and gray levels. It produces the expected results from our process.

• Journal of the Optical Society of Korea
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• 제20권2호
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• pp.239-244
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• 2016

Mugshot face images, routinely collected by police, usually contain both frontal and profile views. Existing automated face recognition methods exploited mugshot databases by enlarging the gallery with synthetic multi-view face images generated from the mugshot face images. This paper, instead, proposes to match the query arbitrary view face image directly to the enrolled frontal and profile face images. During matching, the 3D face shape model reconstructed from the mugshot face images is used to establish corresponding semantic parts between query and gallery face images, based on which comparison is done. The final recognition result is obtained by fusing the matching results with frontal and profile face images. Compared with previous methods, the proposed method better utilizes mugshot databases without using synthetic face images that may have artifacts. Its effectiveness has been demonstrated on the Color FERET and CMU PIE databases.

• 한국멀티미디어학회논문지
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• 제24권4호
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• pp.558-568
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• 2021

The digital image to be accepted as legal evidence, it is important to verify the authentication of the digital image. This study proposes a method of authenticating digital images through three steps of comparing the file structure of digital images taken with iPhone, analyzing the encoding information as well as media logs of the iPhone storing the digital images. For the experiment, digital image samples were acquired from nine iPhones through a camera application built into the iPhone. And the characteristics of file structure and media log were compared between digital images generated on the iPhone and digital images edited through a variety of image editing tools. As a result of examining those registered during the digital image creation process, it was confirmed that differences from the original characteristics occurred in file structure and media logs when manipulating digital images on the iPhone, and digital images take with the iPhone. In this way, it shows that it can prove its forensic authentication in iPhone.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1624-1631
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• 2021

With the continued development of image processing technology, we live in a time when it is difficult to visually discriminate processed (or tampered) images from real images. However, as the risk of fake images being misused for crime increases, the importance of image forensic science for identifying fake images is emerging. Currently, various deep learning-based identifiers have been studied, but there are still many problems to be used in real situations. Due to the inherent characteristics of deep learning that strongly relies on given training data, it is very vulnerable to evaluating data that has never been viewed. Therefore, we try to find a way to improve generalization ability of deep learning-based fake image identifiers. First, images with various contents were added to the training dataset to resolve the over-fitting problem that the identifier can only classify real and fake images with specific contents but fails for those with other contents. Next, color spaces other than RGB were exploited. That is, fake image identification was attempted on color spaces not considered when creating fake images, such as HSV and YCbCr. Finally, dropout, which is commonly used for generalization of neural networks, was used. Through experimental results, it has been confirmed that the color space conversion to HSV is the best solution and its combination with the approach of increasing the training dataset significantly can greatly improve the accuracy and generalization ability of deep learning-based identifiers in identifying fake images that have never been seen before.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2008년도 공동추계학술대회
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• pp.245-246
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• 2008

The goal of this study is to explore the possibility of KLT tracker for tracking the features between two images including rotation and shift. As a test site, Jangsu-Gun area of South Korea is selected and the images taken from UAV camera are used for analysis. The analysis was carried out using KLT tracker developed in a PC environment. The results of the experiment used two images with the large overlapping area are compared with the results of two images with the little overlapping area and rotation. Overall, the research indicates that the integrated features of littlerotation and motion images can significantly increase during the tracking process. But using KLT tracker for extracting and tracking features between images with large rotation and motion, the number of tracked features are decreased.

• 대한인간공학회지
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• 제10권1호
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• pp.11-22
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• 1991

This paper aims to examine experimentally the difference of subjectively measured degree of depth between two dimensional (2D) and three dimensional (3D) images. For this paper, two experiments were conducted; in the first experiment, the subjects were asked to estimate the distance between two objects presented with different depths, while in the second experiment, the subjects' role was to rank three objects in the order of distance from the screen. In both experiments, the objects were presented either in 2D or 3D images. The results of the experiments show that the use of 3D images can induce more accurate and more stable estimates of distance than the use of 2D images. However, it is also noted that the absolute degree of depth is not the unique criteria utilized by the subjects for the distinction of small differences of depth.

• 한국멀티미디어학회논문지
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• 제7권12호
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• pp.1745-1753
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• 2004

A method of estimating the pose of a three-dimensional object from a set of two-dimensioal images based on parametric eigenspace method is proposed. A Gaussian blurred edge image is used as an input image instead of the original image itself as has been used previously. The set of input images is compressed using K-L transformation. By comparing the estimation errors for the original, blurred original, edge, and blurred edge images, we show that blurring with the Gaussian function and the use of edge images enhance the data compression ratio and decrease the resulting from smoothing the trajectory in the parametric eigenspace, thereby allowing better pose estimation to be achieved than that obtainable using the original images as it is. The proposed method is shown to have improved efficiency, especially in cases with occlusion, position shift, and illumination variation. The results of the pose angle estimation show that the blurred edge image has the mean absolute errors of the pose angle in the measure of 4.09 degrees less for occlusion and 3.827 degrees less for position shift than that of the original image.

• 한국음향학회지
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• 제15권6호
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• pp.73-80
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• 1996

얼굴 인식 시스템에서 어떤 인식 파라미터를 사용하느냐에 따라 그 시스템의 성공여부가 판가름난다. 일반적으로 얼굴영상은 조명 상태 등과 같은 주변 환경에 따라 인식 파라미터가 영향을 받는다. 이를 해결하기 위해서는 측면 영상은 주위의 휘도변화에 다소 둔감하므로 측면 영상에서 특징을 추출하여 정면 영상에서의 문제점을 보완하는 것이 올바른 접근 방식이라 여겨진다. 본 논문에서는 이같이 정면영상과 측면영상의 정보를 보완, 취합하는 방식을 제안하고자하며 이를 여러 가지 방법들과 비교, 고찰함으로써 본 논문의 유용성을 입증하고자 한다.

• Journal of Advanced Marine Engineering and Technology
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• 제28권8호
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• pp.1185-1194
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• 2004

Virtual images for PIV are produced for the construction of a benchmark test tool of PTV systems, Camera parameters obtained by an actual experiment are used to construct the virtual images, LES(Large Eddy Simulation) data sets of a channel flow are used for generation of the virtual images, Using the virtual images and the camera's parameters. three-dimensional velocity vectors are obtained for a channel flow. The capabilities of a 3D-PTV algorithm are investigated by comparing the results obtained by the virtual images and those by an actual measurement for the channel flow.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.201-204
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• 2005

Recently, the generation of panoramic images and high quality mosaic images from video sequences has been attempted by a variety of investigations. Among a matter of investigation, in this paper, left and right stereo mosaic image generation utilizing airborne-video sequence images is focused upon. The stereo mosaic image is generated by creating left and right mosaic image which is generated by front and rear slit having different viewing angle in consecutive video frame images. The generation of stereo mosaic image proposed in this paper consists of several processes: camera parameter estimation for each video frame image, rectification, slicing, motion parallax elimination and image mosaicking. However it is necessary to check the feasibility on generating stereo mosaic image as explained processes. Therefore, in this paper, we performed the feasibility test on generating stereo mosaic image using video frame images. In doing so, anaglyphic image for stereo mosaic images is generated and tested for feasibility check.