• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.224-226
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• 2010

컴퓨터 생성 홀로그램(computer-generated hologram, CGH) 기법은 광학 신호들을 근사화한 후 PC에서 수학적인 연산으로 디지털 홀로그램을 생성하는 기술이다. 본 논문에서는 CGH 기법을 하드웨어로 구현할 경우 완벽한 병렬처리와 파이프라이닝이 가능하도록 연산식을 최적화하는 방법을 제안한다. 제안한 방법은 홀로그램의 이전 좌표에서 계산된 값에 일정한 값을 더하여 홀로그램을 생성하는 반복가산 기법의 일반항을 분석하여 하드웨어에 최적화된 수식으로 변형하는 것이다. 최적화된 수식의 경우 현재 좌표의 홀로그램을 계산하기 위해 이전 좌표에서 연산되었던 결과값을 기다렸다 이용하지 않기 때문에 실시간 디지털 홀로그래피를 위한 전용 하드웨어의 설계에 적합할 것이다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.322-324
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• 2011

컴퓨터-생성 홀로그램(computer-generated hologram, CGH) 기법은 실사객체 혹은 가상의 객체로부터 계산에 의해 디지털 홀로그램을 생성해 낼 수 있다. 하지만 HD급 해상도의 디지털 홀로그램 한 프레임을 일반적인 PC를 이용해 계산하기 위해서는 약 10분 정도가 소요된다. 이는 실시간 홀로그래픽 비디오 서비스를 어렵게 하는 문제점 중에 하나이다. 본 논문에서는 CGH 기법의 과도한 연산량을 줄이기 위해 깊이정보(depth-map) 비디오 프레임간의 공간적인 중복성을 이용하는 방법을 제안한다. 이 방법은 인접한 깊이정보 프레임간의 차이를 구해 동일한 깊이값을 갖는 좌표들의 CGH 계산을 생략하는 것이다. 제안한 방법을 적용한 결과 연산속도가 52%정도 향상되는 것을 확인할 수 있었다.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.2
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• pp.29-32
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• 2012

Computer generated holography (CGH) is technology for generating holograms of synthetic, three dimensional (3D) objects which may not exist in the physical world. The process, however, requires heavy amount of computation as the resolution of a hologram is significantly higher than that of a typical optical image. This paper reviews four modern techniques for fast generation of digital Fresnel holograms which are important in the development of holographic video systems. The methods that will be described include the virtual window, sub-line, wavefront recording plane (WRP), and the interpolative WRP schemes. These works share the common objective to generate digital Fresnel hologram at a speed that is close to the video frame rate, and with complexity which is realizable with affordable computing and reconfigurable hardware devices. The author will present the principles and realization of these works, as well as some potential area of research in digital holography.

• Journal of the Optical Society of Korea
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• v.4 no.1
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• pp.19-22
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• 2000

A new image encoding and identification scheme is proposed for security verification by us-ing a CGH(computer generated hologram), random phase mask, and a correlation technique. The encrypted image, which is attached to the security product, is made by multiplying a QP- CGH(quadratic phase CGI) with a random phase function. The random phase function plays a key role when the encrypted image is decrypted. The encrypted image can be optically recovered by a 2-f imaging system and automatically verified for personal identification by a 4-f correlation system. Simulation results show the proposed method can be used for both the reconstruction of an original image and the recognition of an encrypted image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.115-116
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• 2012

최근 차세대 영상 기술로 홀로그래피가 많은 주목을 받고 있다. 컴퓨터를 이용한 홀로그램 생성 방법(computer generated hologram, CGH)을 많이 사용하고 있는데 CGH는 많은 연산량이 요구되기 때문에 실시간의 CGH를 위해서 FPGA나 GPU를 이용한 연산 방법이 주로 사용되고 있다. 하드웨어를 기반으로 하여 구현할 경우에 내부 시스템의 비트 제한으로 인하여 S/W와 같은 품질을 얻을 수 없다. 따라서 본 논문에서는 품질의 저하를 최소화하면서 하드웨어의 자원을 최대한 감소시킬 수 있는 하드웨어 비트 너비를 분석하여 가이드라인을 제시하고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.109-110
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• 2012

본 논문에서는 홀로그램을 실시간으로 생성하기 위하여 수정된 디지털 홀로그램(computer-generated hologram, CGH) 수식을 재정의 하여 3단계로 나누고 2차원 블록 단위 기반의 컴퓨터 생성 홀로그램 생성기의 하드웨어 구조를 제안하였다. 유효광원의 대한 z축 항에 대하여 연산하는 공통항 연산기와 x,y축을 연산하는 죄표값 연산기 마지막으로 각 화소의 대하여 연산하는 화소값 연산기로 이루어진 하드웨어를 제안하고 구현 하였다. 구현한 하드웨어는 $32{\times}32$ 중간 블록의 구조를 가질 때 기존 연구에 비하여 86%이상의 DSP블록을 줄일 수 있다.

• Korean Journal of Optics and Photonics
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• v.13 no.6
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• pp.537-542
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• 2002

Null tests using two different kinds of null corrector have been discussed. A parabolic mirror was used as a surface under test. After designing, encoding, and fabricating the CGH (computer generated hologram), the null CGH test was performed. An autocollimation test was also performed using a flat mirror. The reliability of the null CGH test has been discussed by comparing the result obtained by both null tests.

• Journal of the Optical Society of Korea
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• v.13 no.4
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• pp.445-450
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• 2009

Fingerprint recognition using a joint transform correlator (JTC) is the most well-known technology among optical fingerprint recognition methods. The JTC method optically compares the reference fingerprint image with the sample fingerprint image then examines match or non-match by acquiring a correlation peak. In contrast to the JTC method, this paper presents a new method to examine fingerprint recognition by producing a computer generated hologram (CGH) of those two fingerprint images and directly comparing them. As a result, we present some parameters to show that fingerprint recognition capability of the CGH direct comparison method is superior to that of the JTC method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.257-263
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• 1986

A laser scanner utilizing a computer-generated hologram(CGH) as beam deflector is reported. The CGH optical element has been used mainly for under-filled scanning. Here, a CGH optical element for overfilled scanning is proposed. It can achieve, under the same limitation of fabrication accuracy, better resolution and longer scan length than those for under-filled scanning. Measured scanning characteristics of the laser scanner show the scan length of 40 cm and the beam diameter of 100\ulcorner, where the designed minimum distance between the lines of CGH is 8\ulcorner.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.31-41
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• 2023

Directly converting the focal depth and image size of computer-generated-hologram (CGH), which is obtained by calculating the interference pattern of light from the 3D image, is known to be quite difficult because of the less similarity between the CGH and the original image. This paper proposes a method for separately converting the each of focal length of the given CGH, which is composed of multi-depth images. Firstly, the proposed technique converts the 3D image reproduced from the CGH into a Light-Field (LF) image composed of a set of 2D images observed from various angles, and the positions of the moving objects for each observed views are checked using an object detection algorithm YOLOv5 (You-Only-Look-Once-version-5). After that, by adjusting the positions of objects, the depth-transformed LF image and CGH are generated. Numerical simulations and experimental results show that the proposed technique can change the focal length within a range of about 3 cm without significant loss of the image quality when applied to the image which have original depth of 10 cm, with a spatial light modulator which has a pixel size of 3.6 ㎛ and a resolution of 3840⨯2160.