人體熱紅外線影像的頻譜與非線性特徵提取

Spectral and Nonlinear Feature Extraction from Human Thermal Infrared Imaging

楊祐綱(You Gang Yang)

指導教授 ： 劉偉名

國立中正大學/工學院/資訊工程學系/碩士(2014年)

摘要

近年來人體生物電訊號的研究在生醫應用與臨床研究上有著重要的地位，以心電訊號與血氧濃度為首應用了許多分析方法，像是頻率頻譜分析與非線性分析等，並證明心電訊號與血氧濃度訊號會反映出人體的病理情況。另一方面，以熱紅外線成像紀錄心血管組織，來輔佐病理分析的非侵入式方法，也相繼應用在多種領域。
本文的研究目標是結合近年生醫信號的分析方法，並應用於熱紅外線影像處理上，觀察熱成像的資訊是否也含有心電訊號與血氧濃度訊號的特徵。研究流程可粗略分成：1. 影像套合。2. 訊號前處理。3. 頻率與非線性分析。4. 對應影像結果。頻率與非線性分析包含：傅立葉轉換(FFT, Fourier transform)、小波轉換(WT, wavelet transform)、希爾伯特黃轉換(HHT, Hilbert-Huang transform)，近似熵(ApEn, approximate entropy)與里亞普諾夫指數(LE, Lyapunov exponent)。
本文提出一套實驗與資料處理流程，來分析熱紅外線影像流，以溫度振盪的頻率與非線性特徵差異達到影像增強，並探討溫度訊號與不同人體組織的關係，以靜置攝影來達到組織區分的效果，實驗結果揭示了，單純靜置攝影的溫度資訊就可以將皮膚大血管與皮膚組織區分出來，同時這兩種組織的非線性特徵也是不同的。

關鍵字

非線性分析 ； 希爾伯特黃轉換 ； 小波轉換 ； 傅利葉轉換 ； 熱紅外線成像 ； 血管

並列摘要

In recent years, the research of human bioelectric signals plays an important role in biomedical applications and clinical research . The Electrocardiography (ECG) signal and blood oxygen concentration measurements applied many analysis techniques such as frequency spectrum analysis and nonlinear analysis and proved that ECG signal and blood oxygen signal can reflect the pathological states of the human body. On the other hand, using thermal infrared imaging or other non-invasive methods to observe vasculature are also of interest in many fields.
In the study we took the analysis techniques from biomedical signal fields and applied them to the thermal infrared imaging research to see if the thermal signals share similar characteristics of the ECG signal or the blood oxygen concentration. The whole study can be roughly divided into: (1) Image registration. (2) Signal preprocessing. (3) Frequency and nonlinear analysis. (4) express results in terms of images. Frequency and nonlinear analysis methods includes: Fast Fourier Transform (FFT), wavelet transform (WT), Hilbert-Huang Transform (HHT), approximate entropy (ApEn) and Lyapunov exponent (LE).
This thesis presents a framework to analyze input thermal image streams. We use temperature oscillations in frequency domain and nonlinear characteristics to enhance image contrast, and discuss the relationship between different human tissues. The experimental results reveal that baseline information in static video recording can distinguish long saphenous vein from skin tissue, and the nonlinear characteristics of these two tissues are different.

並列關鍵字

nonlinear analysis ； Hilbert-Huang Transform ； Fourier transform ； Wavelet transform ； vasculature ； Thermal infrared imaging

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