• ETRI Journal
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• 제27권3호
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• pp.289-293
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• 2005

We propose an asymmetric integral imaging method to adjust the resolution and depth of a three-dimensional image. Our method is obtained by use of two lenticular sheets with different pitches fabricated under the same F/#. The asymmetric integral imaging is the generalized version of integral imaging, including both conventional integral imaging and one-dimensional integral imaging. We present experimental results to test and verify the performance of our method computationally.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
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• pp.1250-1253
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• 2009

Integral imaging provides an efficient way to display three-dimensional images with high degree of viewing freedom. Pickup process of integral imaging can also be utilized to acquire three-dimensional contents for displays. This paper introduces basic principle and recent progress of integral imaging technique.

• 한국통신학회논문지
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• 제34권10B호
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• pp.1124-1132
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• 2009

본 논문은 집적영상의 요소영상을 초해상도 영상복원에 이용하여 집적영상의 해상도를 향상시키는 방법을 제안한다. 집적영상에서 전체 요소영상의 인접한 단일 요소영상들 사이에는 대상물체의 동일한 부분의 상을 포함하는 공통부분이 존재한다. 이러한 공통부분들을 초해상도 영상복원의 저해상도 영상으로 이용하게 되면 CCD(Charge Coupled Device) 등의 영상취득 장치의 제한된 해상도로 인한 집적영상의 낮은 해상도 문제를 보완 할 수 있게 된다. 전체 요소영상과 제안된 방법을 이용하여 해상도를 향상시킨 전체 요소영상을 비교하여 제안된 방법의 타당성을 증명하였다.

• Journal of the Optical Society of Korea
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• 제15권4호
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• pp.357-361
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• 2011

Photon-counting sensing is a widely used technique for low-light-level imaging applications. This paper proposes a distance information extraction method with photon-counting passive sensing under low-lightlevel conditions. The photo-counting passive sensing combined with integral imaging generates a photon-limited elemental image array. Maximum-likelihood estimation (MLE) is used to reconstruct the photon-limited image at certain depth levels. The distance information is extracted at the depth level that minimizes the sum of the standard deviation of the corresponding photo-events in the elemental image array. Experimental and simulation results confirm that the proposed method can extract the distance information of the object under low-light-level conditions.

• ETRI Journal
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• 제38권3호
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• pp.502-509
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• 2016

Feature detection and description are key ingredients of common image processing and computer vision applications. Most existing algorithms focus on robust feature matching under challenging conditions, such as inplane rotations and scale changes. Consequently, they usually fail when the scene is blurred by camera shake or an object's motion. To solve this problem, we propose a new feature description algorithm that is robust to image blur and significantly improves the feature matching performance. The proposed algorithm builds a feature descriptor by considering the integral projection along four angular directions ($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, and $135^{\circ}$) and by combining four projection vectors into a single highdimensional vector. Intensive experiment shows that the proposed descriptor outperforms existing descriptors for different types of blur caused by linear motion, nonlinear motion, and defocus. Furthermore, the proposed descriptor is robust to intensity changes and image rotation.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.248-253
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• 2008

In this paper, a novel vehicle detection algorithm is proposed that utilizes the color histogram of the image. The color histogram is used to search the image for regions with shadow, block symmetry, and block non-homogeneity, thereby detecting the vehicle region. First, an integral histogram of the input image is computed to decrease the amount of required computation time for the block color histograms. Then, shadow detection is performed and the block symmetry and block non-homogeneity are checked in a cascade manner to detect the vehicle in the image. Finally, the proposed scheme is applied to both still images taken in a parking lot and an on-road video sequence to demonstrate its effectiveness.

• 한국정보통신학회논문지
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• 제18권11호
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• pp.2799-2804
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• 2014

본 논문에서는 집적 영상 기술을 사용하여 3차원 정보를 추출하는 지도 시스템을 제안한다. 집적 영상 기술은 렌즈 배열을 가지는 2차원 영상 획득장치를 사용하여 다수의 서로 다른 원근감을 가지는 요소 영상을 기록하고 이를 이용하여 3차원 정보를 획득하고 디스플레이하는 기술이다. 본 논문에서는 각 요소 영상간의 위치 차이를 절대 차이의 합 (Summation of Absolute Difference: SAD)를 사용하여 구하고 이를 이용하여 3차원 정보를 추출한다. 따라서, 3차원 물체의 높이 정보를 구할 수 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.683-688
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• 2008

The emotional information processing is to simulate and recognize human sensibility, sensuality or emotion, to realize natural and harmonious human-machine interface. This paper proposes an emotion-based image retrieval method. In this method, user can choose a linguistic query among some emotional adjectives. Then the system shows some corresponding representative images that are pre-evaluated by experts. Again the user can select a representative one among the representative images to initiate traditional content-based image retrieval (CBIR). By this proposed method any CBIR can be easily expanded as emotion-based image retrieval. In CBIR of our system, we use several color and texture visual descriptors recommended by MPEG-7. We also propose a fuzzy similarity measure based on Choquet integral in the CBIR system. For the communication between system and user, a relevance feedback mechanism is used to represent human subjectivity in image retrieval. This can improve the performance of image retrieval, and also satisfy the user's individual preference.

• Journal of information and communication convergence engineering
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• 제13권4호
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• pp.275-279
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• 2015

There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.