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一般影像及紅外線體溫圖之自動化過敏性黑眼圈定位與量化估測
Thesis

一般影像及紅外線體溫圖之自動化過敏性黑眼圈定位與量化估測

黃亭瑜
Masters, National Tsing Hua University
2010

Abstract

紅外線體溫圖過敏性黑眼圈定位 Infrared Thermal ImageAllergic ShinersLocation
Nowadays, the combination of computer technology and medical technology is an unstoppable trend. By using the computerized method, we can quantify and store the medical data automatically and systematically. The quantized data is an objective measurement that can be used to help doctors diagnose the symptoms of allergic disease beyond their professional judgment.In this thesis, we are concerned about how to find a fully automatic method to detect and quantize the region of allergic shiners. Beside experimenting in the visible CCD images we generally used, we will also investigate the possibility of detecting the region of shiners in the infrared thermal images. We developed a method to locate the region of shiner automatically in visible CCD images and then quantize the area and darkness of the detected shiner region. Since the eyes is difficult to locate in IR image, we propose to register the CCD image and IR image first, and then use the location information of eyes which has been detected in CCD image to locate the eyes in IR image. Once we know the location of eyes in IR images, the high-temperature region of the infraorbital area can be located. Finally, we compare the quantized results of the two kinds of images in order to find out the relationship between the region of high-temperature and region of allergic shiner in order to determine whether we can detect a reasonable region of shiner in IR image or not.In this thesis, we can fully automatically locate the region of shiners in both CCD images and IR images, even with the unstandardized data. By comparing the quantized results, we can find out the relationship between the region of high-temperature observed in IR images and region of allergic shiner observed in CCD images. The method we proposed to register the CCD images and IR images can help us locate the facial features in IR image in an unsupervised way. It will be useful for future works which also apply on IR face images.

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