• Title/Summary/Keyword: Low-DOF(Depth Of Field) image

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Fast Extraction of Objects of Interest from Images with Low Depth of Field

  • Kim, Chang-Ick;Park, Jung-Woo;Lee, Jae-Ho;Hwang, Jenq-Neng
    • ETRI Journal
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    • v.29 no.3
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    • pp.353-362
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    • 2007
  • In this paper, we propose a novel unsupervised video object extraction algorithm for individual images or image sequences with low depth of field (DOF). Low DOF is a popular photographic technique which enables the representation of the photographer's intention by giving a clear focus only on an object of interest (OOI). We first describe a fast and efficient scheme for extracting OOIs from individual low-DOF images and then extend it to deal with image sequences with low DOF in the next part. The basic algorithm unfolds into three modules. In the first module, a higher-order statistics map, which represents the spatial distribution of the high-frequency components, is obtained from an input low-DOF image. The second module locates the block-based OOI for further processing. Using the block-based OOI, the final OOI is obtained with pixel-level accuracy. We also present an algorithm to extend the extraction scheme to image sequences with low DOF. The proposed system does not require any user assistance to determine the initial OOI. This is possible due to the use of low-DOF images. The experimental results indicate that the proposed algorithm can serve as an effective tool for applications, such as 2D to 3D and photo-realistic video scene generation.

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An Efficient Object Extraction Scheme for Low Depth-of-Field Images (낮은 피사계 심도 영상에서 관심 물체의 효율적인 추출 방법)

  • Park Jung-Woo;Lee Jae-Ho;Kim Chang-Ick
    • 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.

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Experimental realization of an imaging system using wavefront coding in mobile phone camera (휴대폰용 카메라 모듈에서 파면코딩을 통한 이미지 시스템 실험구현)

  • Kim, Jong-Pil;Lee, Sang-Hyuck;Park, No-Cheol;Park, Young-Pil;Park, Kyoung-Su
    • Transactions of the Society of Information Storage Systems
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    • v.5 no.1
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    • pp.36-40
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    • 2009
  • We describe the experimental realization of image system using wavefront coding in 3-Mega pixel mobile phone camera. We designed aspheric lens to extend the depth of field (DOF) using wavefront coding. In addition, through the aspheric lens and lens barrel manufacturing, we obtained a raw image from a camera module. In our method, the acquired images are restored in the spatial frequency domain using the proposed filter and the spatial frequency response (SFR) is calculated. The proposed filters are composed of image denoising filter using low band pass filter in frequency domain and restoration filter for image restoration. Finally, we achieve an enhanced image by super-resolution image processing. Visual examples are given to demonstrate the performance of the proposed filter.

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Optical Properties Correction of a Heterogeneous Stereoscopic Camera (이종 입체 영상 카메라의 광학 특성 일치화)

  • Jung, Eun Kyung;Baek, Seung-Hae;Park, Soon-Yong;Jang, Ho-Wook
    • 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.

A Revised Dynamic ROI Coding Method Based On The Automatic ROI Extraction For Low Depth-of-Field JPEG2000 Images (낮은 피사계 심도 JPEG2000 이미지를 위한 자동 관심영역 추출기반의 개선된 동적 관심영역 코딩 방법)

  • Park, Jae-Heung;Kim, Hyun-Joo;Shim, Jong-Chae;Yoo, Chang-Yeul;Seo, Yeong-Geon;Kang, Ki-Jun
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.63-71
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    • 2009
  • In this study, we propose a revised dynamic ROI (Region-of-Interest) coding method in which the focused ROI is automatically extracted without help from users during the recovery process of low DOF (Depth-of-Field) JPEG2000 image. The proposed method creates edge mask information using high frequency sub-band data on a specific level in DWT (Discrete Wavelet Transform), and then identifies the edge code block for a high-speed ROI extraction. The algorithm scans the edge mask data in four directions by the unit of code block and identifies the edge code block simply and fastly using a edge threshold. As the results of experimentation applying for Implicit method, the proposed method showed the superiority in the side of speed and quality comparing to the existing methods.

Automatic Extraction of Focused Video Object from Low Depth-of-Field Image Sequences (낮은 피사계 심도의 동영상에서 포커스 된 비디오 객체의 자동 검출)

  • Park, Jung-Woo;Kim, Chang-Ick
    • 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.

An Automatic ROI Extraction and Its Mask Generation based on Wavelet of Low DOF Image (피사계 심도가 낮은 이미지에서 웨이블릿 기반의 자동 ROI 추출 및 마스크 생성)

  • Park, Sun-Hwa;Seo, Yeong-Geon;Lee, Bu-Kweon;Kang, Ki-Jun;Kim, Ho-Yong;Kim, Hyung-Jun;Kim, Sang-Bok
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.3
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    • pp.93-101
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    • 2009
  • This paper suggests a new algorithm automatically searching for Region-of-Interest(ROI) with high speed, using the edge information of high frequency subband transformed with wavelet. The proposed method executes a searching algorithm of 4-direction object boundary by the unit of block using the edge information, and detects ROIs. The whole image is splitted by $64{\times}64$ or $32{\times}32$ sized blocks and the blocks can be ROI block or background block according to taking the edges or not. The 4-directions searche the image from the outside to the center and the algorithm uses a feature that the low-DOF image has some edges as one goes to center. After searching all the edges, the method regards the inner blocks of the edges as ROI, and makes the ROI masks and sends them to server. This is one of the dynamic ROI method. The existing methods have had some problems of complicated filtering and region merge, but this method improved considerably the problems. Also, it was possible to apply to an application requiring real-time processing caused by the process of the unit of block.