• Proceedings of the Optical Society of Korea Conference
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• 2007.02a
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• pp.24-25
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• 2007

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.409-410
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• 2012

본 논문에서는 디지털 홀로그램의 저작권 보호를 위한 영상암호화 알고리즘을 제안한다. 이 기술은 자연영상과는 상이한 특성을 보이는 디지털 홀로그램의 화소분포를 고려하여, 디지털 홀로그램을 복원영역으로 변환한 후 데이터의 일부분을 암호화 하는 기법이다. 실험결과 제안한 암호화 알고리즘은 디지털 홀로그램 데이터의 일부분만을 조작하여 홀로그래픽 복원영상을 효율적으로 은닉하는 것을 확인할 수 있었다.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2014.11a
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• pp.230-230
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• 2014

디지털 홀로그램 이미징 장치를 이용하여 박막과 웨이퍼 간의 두께 및 하전입자의 분포를 모니터링하는 센서의 성능을 보고한다. 이 센서는 웨이퍼와 SiN 박막 간의 경계를 구분하였으며, 경계에서의 하전입자의 분포의 분석도 가능함을 보였다. 이 센서는 다양한 종류의 계면 내지 박막 내부의 하전입자의 분포의 측정을 가능하게 하며, 또한 두께 변이의 실시간 측정도 가능하게 하여 향후 대량 생산현장에서의 광범위한 응용이 예상된다.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.181-183
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• 2003

We propose a new watermarking scheme that can be used to embed multiple bits and also resilient to JPEG compression and geometrical transforms such as scaling, rotation, and cropping, based on off-axis holographic watermark that allows multiple watermark recovery without original content(cover image). The holographic watermark is that Fourier transformed digital hologram is embedded into cover image in the spatial domain. The proposed method has not only increased robustness with a stronger embedding but also imperceptibility of the watermark in the evaluation process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1588-1594
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• 2020

In this paper, we discuss a data balancing method for learning a neural network that generates digital holograms using a deep neural network (DNN). Deep neural networks are based on deep learning (DL) technology and use a generative adversarial network (GAN) series. The fringe pattern, which is the basic unit of a hologram to be created through a deep neural network, has very different data types depending on the hologram plane and the position of the object. However, because the criteria for classifying the data are not clear, an imbalance in the training data may occur. The imbalance of learning data acts as a factor of instability in learning. Therefore, it presents a method for classifying and balancing data for which the classification criteria are not clear. And it shows that learning is stabilized through this.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.42-54
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• 2023

It is an important issue to compress huge holographic data in a digital format. In particular, research on the compression of phase-only holograms for commercialization is noteworthy. Conventional video coding standards optimized for natural images are not suitable for compressing phase signals, and neural network-based compression model that can be optimized for phase signals can achieve high performance, but has a memory issue in learning high-resolution holographic data. In this paper, we show that by applying a block-based learned image compression model that can solve memory problems to phase-only holograms, the proposed method can demonstrate significant performance improvement over standard codecs even under the same conditions as block-based. Block-based learned compression model can provide compatibility with conventional standard codecs, solve memory problems, and can perform significantly better against phase-only hologram compression.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.425-432
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• 2020

Stereoscopic imaging is an important branch in the field of digital imaging, and has grown significantly over the last two decades through research and development. Hologram projection technology based on stereoscopic technology has been a social issue since the development of the Hungarian physicist Daniel Garber in 1947. It is becoming more and more important as stereoscopic works using similar technologies are applied to various fields. This study analyzed content cases using classical and creative stereoscopic technology from the perspective of digital image content design and explored the multiprotocol direction of holographic projection.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.135-136
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• 2015

컴퓨터 생성 홀로그램(CGH: computer generated hologram) 기법은 기존의 광학계 장치와 변수들을 수학적으로 모델링하여 일반 범용 컴퓨터(PC: personal computer)로도 디지털 홀로그램을 생성할 수 있는 기술이다. 이 기술은 디지털 홀로그램의 해상도와 3D 물체의 광원 수에 따라 알고리즘의 연산량이 좌우되기 때문에, 실용적인 사용을 위해서 알고리즘의 연산량을 낮추거나 하드웨어의 연산 속도를 높이는 연구가 필수적이다. 본 논문에서는 초다광원 3D 물체의 디지털 홀로그램을 고속으로 생성할 수 있는 방법을 제안한다. 제안하는 방법은 한 개의 서버 PC와 다수의 클라이언트 PC들로 구성되어 있으며, 이들은 일반적으로 사용되는 범용 GPU (graphic processing unit)가 장착되어 있다. 서버에서 3D 물체의 광원을 스캔하여 데이터화 하고, 클라이언트 PC들의 연산 능력에 따라 광원 데이터를 분할하여 클라이언트들에게 각각 전송한다. 각각의 클라이언트들은 전송받은 데이터를 이용해 다중 GPU 기반의 CGH 연산을 수행하여 간섭 패턴들을 생성하고, 생성된 패턴들은 다시 서버 PC로 재전송된다. 서버 PC로 재전송 된 패턴들이 하나로 누적되면 디지털 홀로그램이 생성된다. 본 실험에서, 기존의 방법으로는 139,655개의 광원에 대해 $1,024{\times}1,024$ 해상도의 홀로그램을 생성하는데 약 2,250 ms가 걸린 반면, 제안하는 방법은 약 478 ms의 속도로 생성할 수 있음을 확인하였다.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.11
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• pp.67-74
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• 2018

With the rapid increase in the elderly population, numerous problems arise related to the decreased cognitive function such as the declines of reaction time and concentration which are both resulting from ageing. Recently, ICT-based smart home and other residential services are being developed as a means of complementing human cognitive functions, but the elderly, who are in most cases digital-illiterate, find it hard to utilize these tools actively and if so it usually takes longer time and endeavor for the elderly to be familiarized with ICT devices. In this context, this study suggests a configuration of the holographic system in houses that complement the cognitive function of the elderly with the consideration of the interaction with the vision which is a critical function in the cognitive process. The method of this study consists of a literature review on topics including the characteristics of the cognitive function among the elderly, holographic technology and residential services; a configuration of residential services for different space types, depending on the aspects of the cognitive function among the elderly; and finally a suggestion of a holographic system configuration and application depending on various scenarios.

• Journal of the Optical Society of Korea
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• v.16 no.2
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• pp.115-120
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• 2012

In this paper, we present a method to automatically quantify the three-dimensional (3D) volume of red blood cells (RBCs) using off-axis digital holographic microscopy. The RBCs digital holograms are recorded via a CCD camera using an off-axis interferometry setup. The RBCs' phase image is reconstructed from the recorded off-axis digital hologram by a computational reconstruction algorithm. The watershed segmentation algorithm is applied to the reconstructed phase image to remove background parts and obtain clear targets in the phase image with many single RBCs. After segmenting the reconstructed RBCs' phase image, all single RBCs are extracted, and the 3D volume of each single RBC is then measured with the surface area and the phase values of the corresponding RBC. In order to demonstrate the feasibility of the proposed method to automatically calculate the 3D volume of RBC, two typical shapes of RBCs, i.e., stomatocyte/discocyte, are tested via experiments. Statistical distributions of 3D volume for each class of RBC are generated by using our algorithm. Statistical hypothesis testing is conducted to investigate the difference between the statistical distributions for the two typical shapes of RBCs. Our experimental results illustrate that our study opens the possibility of automated quantitative analysis of 3D volume in various types of RBCs.