• Title/Summary/Keyword: Auto blur system

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Isotropic Out-of-focus Blur Estimation and Fully Digital Auto-Focusing Based on A Priori Estimated Set of PSF (등방성 초점열화 추정기법 및 사전 추정 점확산함수 집합을 이용한 완전 디지털 자동 초점 시스템)

  • 황성현;신정호;이성원;백준기
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.235-249
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    • 2004
  • This paper proposes a method for estimating isotropic out-of-focus blur and a fully digital auto-focusing based on a priori estimate set of PSFs. The proposed algorithm for identifying the isotropic PSF is performed by approximating an isotropic blur to a novel discrete PSF model and estimating the PSF model coefficients from degraded edges. After acquiring the set of PSFs by proposed PSF estimation algorithm the proposed fully digital auto-focusing system can restore out-of-focused images by two steps: i) selecting an optimal PSF and ii) restoring the out-of-focused image by digital image restoration.

Real-Time Digital Auto-Focusing Using A-Priori Estimated Point Spread Functions (점 확산 함수 데이터베이스를 이용한 실시간 디지털 자동초점)

  • Yoo Yoon-Jong;Lee Jung-Soo;Shin Jeong-Ho;Paik Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.5 s.311
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    • pp.1-11
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    • 2006
  • This paper presents a digital auto-focusing method using a priori estimated point-spread-functions (PSF) database. The proposed algorithm efficiently removes out-of-focus blur in a degraded input image by selecting the optimal PSF from the database. The database consists of optical characteristics of image formation system. The PSF selection Process is performed based on a novel focusing measure. The proposed method includes a spatially adaptive filter for removing both noise and ringing artifacts. Experimental results show that the proposed method efficiently removes out-of-focus blur using significantly reduced computational load compared with the existing method.

All in focus Camera vision system for Mobile Phone based on the Micro Diffractive Fresnel lens systems (곡률 변경 소자를 이용한 All In Focus)

  • Chi, Yong-Seok;Kim, Young-Seop
    • Journal of the Semiconductor & Display Technology
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    • v.6 no.3
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    • pp.65-70
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    • 2007
  • A method to focus the object in camera system by applying the Hill climb algorithm from optical lens moving device (VCM; Voice coil motor) is proposed. The focusing algorithm from VCM is focus on the object but in these criteria is a well-known drawback; the focus is good only at same distance objects but the focus is bad (blur image) at different distance objects because of the DOF (Depth of focus) or DOF (Depth of field) at the optical characteristic. Here, the new camera system that describes the Reflector of free curvature systems (or Diffractive Fresnel lens) and the partition of focusing window area is proposed. The method to improve the focus in all areas (different distance objects) is proposed by new optical system (discrete auto in-focus) using the Reflector of free curvature systems (or Diffractive Fresnel lens) and by applying the partition of all areas. The proposal is able to obtain good focus in all areas.

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CNN Based Face Tracking and Re-identification for Privacy Protection in Video Contents (비디오 컨텐츠의 프라이버시 보호를 위한 CNN 기반 얼굴 추적 및 재식별 기술)

  • Park, TaeMi;Phu, Ninh Phung;Kim, HyungWon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.1
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    • pp.63-68
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    • 2021
  • Recently there is sharply increasing interest in watching and creating video contents such as YouTube. However, creating such video contents without privacy protection technique can expose other people in the background in public, which is consequently violating their privacy rights. This paper seeks to remedy these problems and proposes a technique that identifies faces and protecting portrait rights by blurring the face. The key contribution of this paper lies on our deep-learning technique with low detection error and high computation that allow to protect portrait rights in real-time videos. To reduce errors, an efficient tracking algorithm was used in this system with face detection and face recognition algorithm. This paper compares the performance of the proposed system with and without the tracking algorithm. We believe this system can be used wherever the video is used.