• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.86-87
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• 2014

JPEG 표준화 기구에서 표준화 중인 JPEG AR 표준은 증강 현실 응용을 구성하는 요소간의 인터페이스를 표준화하고 있다. 본 논문에서는 증강 현실 기술을 기반으로 기존 미디어에 새롭게 가상 정보를 추가한 증강 미디어 서비스(개인화 서비스, 증강 방송, 사물 인터넷과 결합한 증강 미디어 서비스)를 JPEG AR 표준 측면에서 고찰하고, 이들 서비스를 위한 JPEG AR 표준의 추가 요소를 살펴본다. 세 가지 서비스를 구체적으로 살펴본바, JPEG AR 표준은 기존의 증강 현실 표준보다 유연한 시스템 구조를 갖고 있어 다른 분야 또는 시스템과의 연결이 용이하고, 이에 따라 증강 미디어 서비스뿐 아니라 새로운 융 복합 기술을 창출하는데 일조할 것으로 기대된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.417-424
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• 2019

This paper presents the design of a JPEG-LS codec for lossless image compression from AR/VR device. The proposed JPEG-LS(: LosSless) codec is mainly composed of a context modeling block, a context update block, a pixel prediction block, a prediction error coding block, a data packetizer block, and a memory block. All operations are organized in a fully pipelined architecture for real time image processing and the LOCO-I compression algorithm using improved 2D approach to compliant with the SBT coding. Compared with a similar study in JPEG-LS, the Block-RAM size of proposed STB-FLC architecture is reduced to 1/3 compact and the parallel design of the predication block could improved the processing speed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.75-76
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• 2014

증강 현실(Augmented Reality)은 현실 세계에 어떤 부가 정보가 덧붙여진 현실이다. 증강 현실 응용은 주로 스마트폰에 내장된 카메라를 통해 실시간으로 입력받은 이미지 정보를 분석하거나, GPS 정보, 전자 나침반 정보 등을 이용해서 증강 현실응용에 맞는 부가 정보를 입력받은 영상 위에 덧붙여서 구현한다. 하지만 다양한 회사에서 각자의 방식대로 증강 현실 응용을 구현하기 때문에, 개별적으로 구현된 증강 현실 시스템은 서로 호환이 되지 않고 이는 증강 현실 산업의 발전을 막는 걸림돌이 되고 있다. 이러한 문제점을 해결하고 관련 산업의 활성화를 꾀하고자 JPEG 기반 증강 현실 시스템을 제안하였고, 이 제안은 최근 ISO/IEC JTC1 SC29 WG1(JPEG) 표준화 단체에서 받아들여져 ISO/IEC 19710(JPEG AR) 표준화가 시작되었다.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.263-270
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• 2014

This paper proposes a new metadata schema for effective mobile service of augmented reality technology, which is used in the convergence of media into a frame among the real world image and objects of virtual world. The proposed metadata schema is extended from JPSearch Core Metadata Schema (ISO/IEC 24800-2 International Standard) with analysis of the functionalities under industrial requirements, and enables to provide an effective application in the actual services. In addition, the proposed schema is available to organize the exchange of information between heterogeneous systems. With development of the prototype system, the proposed metadata schema is going to be submitted and verified under ISO/IEC JTC1 SC29 WG1 JPEG AR standard project.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.195-201
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• 2015

For median filtering (MF) detection in altered digital images, this paper presents a new feature vector that is formed from autoregressive (AR) coefficients via an AR model of the gradients between the neighboring row and column lines in an image. Subsequently, the defined 10-D feature vector is trained in a support vector machine (SVM) for MF detection among forged images. The MF classification is compared to the median filter residual (MFR) scheme that had the same 10-D feature vector. In the experiment, three kinds of test items are area under receiver operating characteristic (ROC) curve (AUC), classification ratio, and minimal average decision error. The performance is excellent for unaltered (ORI) or once-altered images, such as $3{\times}3$ average filtering (AVE3), QF=90 JPEG (JPG90), 90% down, and 110% up to scale (DN0.9 and Up1.1) images, versus $3{\times}3$ and $5{\times}5$ median filtering (MF3 and MF5, respectively) and MF3 and MF5 composite images (MF35). When the forged image was post-altered with AVE3, DN0.9, UP1.1 and JPG70 after MF3, MF5 and MF35, the performance of the proposed scheme is lower than the MFR scheme. In particular, the feature vector in this paper has a superior classification ratio compared to AVE3. However, in the measured performances with unaltered, once-altered and post-altered images versus MF3, MF5 and MF35, the resultant AUC by 'sensitivity' (TP: true positive rate) and '1-specificity' (FN: false negative rate) is achieved closer to 1. Thus, it is confirmed that the grade evaluation of the proposed scheme can be rated as 'Excellent (A)'.

• Journal of Satellite, Information and Communications
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• v.8 no.1
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• pp.83-88
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• 2013

Recently, by increasing the number of smartphone users, the applications for product brochure and advertising service using a technology of augmented reality are also taking place exponentially. The term, augmented reality, is an application of providing composite view with real world and virtual world, and synthesizing the information to make it look-like things that exist in the actual environments of the original real world. In this paper, we present the trends of core technologies and the standardization related on augmented reality in the mobile environment, and discuss the necessary of standards related to image-based augmented reality.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.79-84
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• 2015

In a distribution of digital image, there is a serious problem that is a distribution of the altered image by a forger. For the problem solution, this paper proposes a median filtering (MF) image forensic decision algorithm using a feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value' gradients of original image then 1th~6th order coefficients to be six feature vector. And the reconstructed image is produced by the solution of Poisson's equation with the gradients. From the difference image between original and its reconstructed image, four feature vector (Average value, Max. value and the coordinate i,j of Max. value) is extracted. Subsequently, Two kinds of the feature vector combined to 10 Dim. feature vector that is used in the learning of a SVM (Support Vector Machine) classification for MF (Median Filtering) detector of the altered image. On the proposed algorithm of the median filtering detection, compare to MFR (Median Filter Residual) scheme that had the same 10 Dim. feature vectors, the performance is excellent at Unaltered, Averaging filtering ($3{\times}3$) and JPEG (QF=90) images, and less at Gaussian filtering ($3{\times}3$) image. However, in the measured performances of all items, AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.