• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2008년도 International Meeting on Information Display
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• pp.1131-1134
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• 2008

In this invited paper, numerical reconstruction and pattern recognition using integral imaging are overviewed. The computational integral imaging method reconstructs three-dimensional information at arbitrary depth-levels. Photon-counting nonlinear matched filtering combined with the computational reconstruction provides promising results for the application of low-light level recognition.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2008년도 International Meeting on Information Display
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• pp.726-729
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• 2008

In this paper, we present an interference problem among elemental images in computational integral imaging reconstruction. To overcome the interference problem, we propose a method to calculate a minimum magnification factor and the preliminary experiments are performed.

• ETRI Journal
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• 제28권4호
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• pp.521-524
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• 2006

In this letter, we propose a novel computational integral imaging reconstruction technique based on a lenslet array model. The proposed technique provides improvement of viewing images by extracting multiple pixels from elemental images according to ray tracing based on the lenslet array model. To show the feasibility of the proposed technique, we analyze it according to ray optics and present the experimental results.

• 한국정보통신학회논문지
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• 제20권12호
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• pp.2363-2369
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• 2016

본 논문에서는 집적 영상과 컴퓨터 재생 기술을 활용한 3차원 QR 코드 생성 기술을 제안한다. 제안하는 기술에서는 2차원 QR 코드를 네 개의 면으로 나누어 각각의 면을 서로 다른 깊이에 배치한 뒤 깊이가 추가된 3차원 QR 코드를 합성조리개 집적 영상과 컴퓨터 재생 기술을 사용하여 생성한다. 이 과정에서 3차원 영상 기술 중 하나인 집적 영상 기술을 사용한다. 마지막으로, 3차원 QR 코드를 집적영상을 이용하여 컴퓨터 재생을 한 뒤 각 면을 배치했던 깊이 부분에서 영상을 재생하고 조합하면 3차원 QR 코드를 읽을 수 있다. 따라서 QR 코드를 읽을 때 보안을 강화할 수 있다. 본 논문에서는 제안된 기술이 QR 코드를 읽을 때 보안을 강화할 수 있음을 보이기 위하여 광학적 실험과 컴퓨터 재생을 수행하였다. 또한, 재생 깊이를 알고 있을 때, 3차원 QR 코드를 읽을 수 있음을 보였다.

• 한국광학회:학술대회논문집
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• 한국광학회 2007년도 하계학술발표회 논문집
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• pp.257-258
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• 2007

For objective evaluation of computational integral imaging reconstruction (CIIR) schemes, a framework with the computational pickup and the CIIR process using Gaussian images is presented and characteristics of CIIR along the distance between lenslet array and objects are investigated.

• ETRI Journal
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• 제27권6호
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• pp.708-712
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• 2005

We propose a computational reconstruction technique in large-depth integral imaging where the elemental images have information of three-dimensional objects through real and virtual image fields. In the proposed technique, we reconstruct full volume information from the elemental images through both real and virtual image fields. Here, we use uniform mappings of elemental images with the size of the lenslet regardless of the distance between the lenslet array and reconstruction image plane. To show the feasibility of the proposed reconstruction technique, we perform preliminary experiments and present experimental results.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2005년도 International Meeting on Information Displayvol.II
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• pp.1588-1591
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• 2005

In this paper, we propose novel computational reconstruction technique of three-dimensional objects in integral imaging by use of a lenslet array. We applied our technique to two different integral imaging systems according the distance between lenslet array and elemental image plane. Experimental results are presented and discussed as well.

• Journal of the Optical Society of Korea
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• 제12권3호
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• pp.131-135
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• 2008

Computational integral imaging(CII) has the advantage of generating the volumetric information of the 3D scene without optical devices. However, the reconstruction process of CII requires increasingly larger sizes of reconstructed images and then the computational cost increases as the distance between the lenslet array and the reconstructed output plane increases. In this paper, to overcome this problem, we propose a novel CII method using a depth conversion technique. The proposed method can move a far 3D object near the lenslet array and reduce the computational cost dramatically. To show the usefulness of the proposed method, we carry out the preliminary experiment and its results are presented.

• Journal of the Optical Society of Korea
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• 제12권2호
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• pp.88-92
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• 2008

This paper discusses a photon-counting linear discriminant analysis (LDA) with computational integral imaging (II). The computational II method reconstructs three-dimensional (3D) objects on the reconstruction planes located at arbitrary depth-levels. A maximum likelihood estimation (MLE) can be used to estimate the Poisson parameters of photon counts in the reconstruction space. The photon-counting LDA combined with the computational II method is developed in order to classify partially occluded objects with photon-limited images. Unknown targets are classified with the estimated Poisson parameters while reconstructed irradiance images are trained. It is shown that a low number of photons are sufficient to classify occluded objects with the proposed method.

• Journal of the Optical Society of Korea
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• 제18권4호
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• pp.388-394
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• 2014

In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.