• The Journal of the Acoustical Society of Korea
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• v.42 no.1
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• pp.67-74
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• 2023

The images acquired from the speaker's mouth region revealed the unique patterns according to the corresponding voices. By using this principle, the several methods were proposed in which speech signals were recognized or synthesized from the images acquired at the speaker's lower face. In this study, an image-based speech synthesis method was proposed in which the depth images were cooperatively used. Since depth images yielded depth information that cannot be acquired from optical image, it can be used for the purpose of supplementing flat optical images. In this paper, the usefulness of depth images from the perspective of speech synthesis was evaluated. The validation experiment was carried out on 60 Korean isolated words, it was confirmed that the performance in terms of both subjective and objective evaluation was comparable to the optical image-based method. When the two images were used in combination, performance improvements were observed compared with when each image was used alone.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.42-50
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• 2017

A Bit-depth expansion is a method to increase the number of bit. It is getting important as the needs of HDR (High Dynamic Range) display or resolution of display have been increased because the level of luminance or expressiveness of color is proportional to the number of bit in the display. In this paper, we present effective bit-depth expansion algorithm for conventional standard 8 bit-depth content to display in high bit-depth device (10 bits). Proposed method shows better result comparing with recently developed methods in quantitative (PSNR) with low complexity. The proposed method shows 1db higher in PSNR measurement with 40 times faster in computational time.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.502-511
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• 2009

In order to simulate a depth-of-field effect in real world, there have been several researches in computer graphics field. It can represent an out-of-focused scene by calculating focal plane. When a point in a 3D coordinate lies on further or nearer than focal plane, the point is presented as a blurred circle on image plane according to the characteristic of the aperture and the lens. We can generate a realistic image by simulating the effect because it provides an out-of-focused scene like human eye dose. In this paper, we propose a method to calculate a disparity value of a viewer using a customized stereoscopic eye-tracking system and a GPU-based depth-of-field control method. They enable us to generate more realistic images reducing side effects such as dizziness. Since stereoscopic imaging system compels the users to fix their focal position, they usually feel discomfort during watching the stereoscopic images. The proposed method can reduce the side effect of stereoscopic display system and generate more immersive images.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.169-179
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• 2014

In this paper, we propose a DOF (Depth of Field) correction technique by determining the values of the internal parameters of a 3-D camera which consists of stereoscopic cameras of different optical properties. If there is any difference in the size or the depth range of focused objects in the left and right stereoscopic images, it could cause visual fatigue to human viewers. The object size of in the stereoscopic image is corrected by the LUT of zoom lenses, and the forward and backward DOF are corrected by the object distance. Then the F-numbers are determined to adjust the optical properties of the camera for DOF correction. By applying the proposed technique to a main-sub type 3-D camera using a GUI-based DOF simulator, the DOF of the camera is automatically corrected.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.851-861
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• 2006

The paper proposes a novel unsupervised video object segmentation algorithm for image sequences with low depth-of-field (DOF), which is a popular photographic technique enabling to represent the intention of photographer by giving a clear focus only on an object-of-interest (OOI). The proposed algorithm largely consists of two modules. The first module automatically extracts OOIs from the first frame by separating sharply focused OOIs from other out-of-focused foreground or background objects. The second module tracks OOIs for the rest of the video sequence, aimed at running the system in real-time, or at least, semi-real-time. The experimental results indicate that the proposed algorithm provides an effective tool, which can be a basis of applications, such as video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.74-85
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• 2012

In this paper, we propose a optical property correction technique for a low-cost heterogeneous stereoscopic camera. Three main optical properties of a stereoscopic camera are zoom, focus, and DOF(depth of field). The difference or mis-match of these properties between two stereoscopic videos are the main causes of the visual fatigue to human eyes. The proposed correction technique reduces the difference of the optical properties between the stereoscopic videos and produces high-quality stereoscopic videos. To correct the zoom difference, a LUT(look-up table) is established to match the zoom ratio between the stereoscopic videos. To correct the DOF difference, the magnitude of image edge is measured and the lens iris is changed to control the DOF of the camera. A vertical-type stereoscopic rig is developed for the experiments of the optical property correction. Based on the experimental results, we find that a low-cost heterogeneous stereoscopic camera can be implemented, which can yield low visual fatigue to human eyes.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1139-1149
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• 2006

This paper describes a novel and efficient algorithm, which extracts focused objects from still images with low depth-of-field (DOF). The algorithm unfolds into four modules. In the first module, a HOS map, in which the spatial distribution of the high-frequency components is represented, is obtained from an input low DOF image [1]. The second module finds OOI candidate by using characteristics of the HOS. Since it is possible to contain some holes in the region, the third module detects and fills them. In order to obtain an OOI, the last module gets rid of background pixels in the OOI candidate. The experimental results show that the proposed method is highly useful in various applications, such as image indexing for content-based retrieval from huge amounts of image database, image analysis for digital cameras, and video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing system.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.119-124
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• 2008

2000년대 들어 주기적으로 발생하고 있는 봄 가뭄에 대한 적절한 대책 마련을 위해서는 가뭄을 모니터링 할 수 있는 감시체계가 필요하며 가뭄의 심도를 정량적으로 나타내기 위한 지표가 요구된다. 또한, 가뭄의 거동 및 지역적인 심도 분석을 위해서는 면 단위의 공간적인 분석이 요구된다. 위성영상은 공간정보를 신속하고 주기적으로 제공할 수 있는 도구로 위성영상의 밴드 조합을 통해 제작된 식생지수는 1990년대 중반 이후 건조지역을 중심으로 가뭄 모니터링을 위한 도구로 활용 중이다. 본 연구에서는 MODIS 영상으로부터 제작된 정규식생지수(NDVI)를 이용하여 식생상태지수(VCI)와 정규화된 식생지수(SVI)를 제작하였으며 2000년$\sim$2007년을 대상으로 가뭄발생연도, 각 가뭄사상에 대한 심도, 가뭄다발 시기 및 다발지역을 분석하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.253-256
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• 2021

본 논문에서는 합성곱 신경망을 통해 학습된 DoF(피사계 심도, Depth of field) 네트워크 아키텍처를 이용하여 객체 인식, 시점 추적, 문자 인식, 비사실적 렌더링 등 다양한 애플리케이션에 적용할 수 있는 사후 필터링 기법에 대해 살펴본다. 일반적으로 영상은 포커싱과 아웃포커싱에 의해 사용자의 관심표현이 결정되며, 이를 이용하여 영상 내 중요도를 판단한다. 영상 내에는 수많은 콘텐츠들이 혼재되어 있기 때문에 사용자가 집중적으로 보고 있는 콘텐츠를 찾아내기 어렵다. 본 논문에서는 사용자가 흥미롭고 집중적으로 보고 있는 영역을 DoF 네트워크로 학습시키고, 이를 통해 이전 기법으로는 표현할 수 없었던 DoF 기반 객체 인식, 시점 추적, 문자 인식, 비사실적 렌더링을 효율적으로 표현해낸다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.435-437
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• 2010

렌즈의 피사계심도 (Depth of Field)가 낮은 카메라로 영상을 획득 했을 때, 한 영상 내에도 in-focus 영역과 out of-focus 영역이 동시에 존재하게 된다. 따라서 영상을 복원하기 위해 in-focus 영역과 out-of-focus 영역을 구분하는 focus measure가 필요하게 된다. 기존 focus measure 알고리즘은 획득된 영상의 intensity 값의 절대적인 변화나 고주파수 성분 값에 따라 in-focus와 out-of-focus를 결정하기 때문에 out-of-focus 영역이 smooth 하지 않을 경우에는 in-focus 영역이라 잘못 판단할 수 있을 뿐만 아니라 잡음에 민감한 단점을 가진다. 본 논문에서는 기존 알고리즘의 한계점을 보완하는 연구 방향을 제시한다.