• Journal of the Korean Society of Radiology
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• v.6 no.1
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• pp.73-77
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• 2012

Recently, Interest to the photoconductor, which is used to flat form X-ray detector such as a-Se, $HgI_2$, PbO, CdTe, $PbI_2$ etc. is increasing. In this study, the film layer by using the photoconductive material with particle sedimentation was fabricated and evaluated. The quantization efficiency of the continuous X-ray with the 70 kVp energy bandwidth was analyzed by using the Monte Carlo simulation. With the results, the thickness of film with 64 % quantization efficiency was 180 ${\mu}m$ which is similar to the efficiency of 500 ${\mu}m$ a-Se film. And $HIg_2$ film has the high quantization efficiency of 74 % on 240 ${\mu}m$ thickness. The electrical characteristics of the 239 ${\mu}m$ $Hgl_2$ films produced by particle sedimentation were shown as very low dark current(under 10 $pA/mm^2$), and high sensitivity(19.8 mC/mR-sec) with 1 $V/{\mu}m$ input voltage. The SNR, which is influence to the contrast of X-ray image, was shown highly as 3,125 in low driving voltage on 0.8 $V/{\mu}m$. With the results of this study, the development of the low-cost, high-performance image detector with film could be possible by replacing the film produced by particle sedimentation instead to a-Se detector.

• 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).