• Title/Summary/Keyword: Multimedia Security

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Analysis on Subjective Image Quality Assessments for 4K-UHD Video Viewing Environments (4K-UHD 비디오 시청환경 특성분석을 위한 주관적 화질평가 분석)

  • Park, In-Kyung;Ha, Kwang-Sung;Kim, Mun-Churl;Cho, Suk-Hee;Cho, Jin-Soo
    • Journal of Broadcast Engineering
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    • v.15 no.4
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    • pp.563-581
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    • 2010
  • In this paper, we perform subjective visual quality assessments on UHD video for UHD TV services and analyze the assessment results. Demands for video services have been increased with availabilities of DTV, Internet and personal media equipments. With this trend, the demands for high definition video have also been increasing. Currently, 2K-HD ($1920{\times}1080$) video have been widely consumed over DTV, DVD, digital camcoders, security cameras and other multimedia terminals in various types, and recently digital cinema contents of 4K-UHD($3840{\times}2160$) have been popularly produced and the cameras, beam projects, display panels that support for 4K-UHD video start to come out into multimedia markets. Also it is expected that 4K-UHD service will appear soon in broadcasting and telecommunications environments. Therefore, in this paper, subjective assessments of visual quality on resolutions, color formats, frame rates and compression rates have been carried to provide basis information for standardization of signal specification of UHD video and viewing environments for future UHDTV. As the analysis on the assessments, UHD video exhibits better subjective visual quality than HD by the evaluators. Also, the 4K-UHD test sequences in YUV444 shows better subjective visual quality than the 4K-UHD test sequences in YUV422 and YUV420, but there is little perceptual difference on 4K-UHD test sequences between YUV422 and YUV420 formats. For the comparison between different frame rates, 4K-UHD test sequences of 60fps gives better subjective visual quality than those of 30fps. For bit-depth comparison, HD test sequences in 10-bit depth were little differentiated from those in 8-bit depth in subject visual quality assessment. Lastly, the larger the PSNR values of the reconstructed 4K-UHD test sequences are, the higher the subjective visual quality is. Against the viewing distances, the differences among encoded 4K-UHD test sequences were less distinguished in longer distances from the display.

A Study on Fast Iris Detection for Iris Recognition in Mobile Phone (휴대폰에서의 홍채인식을 위한 고속 홍채검출에 관한 연구)

  • Park Hyun-Ae;Park Kang-Ryoung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.2 s.308
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    • pp.19-29
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    • 2006
  • As the security of personal information is becoming more important in mobile phones, we are starting to apply iris recognition technology to these devices. In conventional iris recognition, magnified iris images are required. For that, it has been necessary to use large magnified zoom & focus lens camera to capture images, but due to the requirement about low size and cost of mobile phones, the zoom & focus lens are difficult to be used. However, with rapid developments and multimedia convergence trends in mobile phones, more and more companies have built mega-pixel cameras into their mobile phones. These devices make it possible to capture a magnified iris image without zoom & focus lens. Although facial images are captured far away from the user using a mega-pixel camera, the captured iris region possesses sufficient pixel information for iris recognition. However, in this case, the eye region should be detected for accurate iris recognition in facial images. So, we propose a new fast iris detection method, which is appropriate for mobile phones based on corneal specular reflection. To detect specular reflection robustly, we propose the theoretical background of estimating the size and brightness of specular reflection based on eye, camera and illuminator models. In addition, we use the successive On/Off scheme of the illuminator to detect the optical/motion blurring and sunlight effect on input image. Experimental results show that total processing time(detecting iris region) is on average 65ms on a Samsung SCH-S2300 (with 150MHz ARM 9 CPU) mobile phone. The rate of correct iris detection is 99% (about indoor images) and 98.5% (about outdoor images).