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								\section{Performance Evaluation}
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								\label{sec:eval}
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								To evaluate the effectiveness of the proposed method, we did the different ratios of compressing on a thermal data by our method compared to JPEG image using different quality and png image, a lossless bit map image. We set the camera at the ceiling and view direction is perpendicular to the ground, and the thermal data size is $480 \times 640$ pixels. The JPEG image is generated by OpenCV $3.3.0$ which is using libjpeg version 9 13-Jan-2013, and image quality from $1$ to $99$.
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								Figure~\ref{fig:4KMy} and Figure~\ref{fig:4KJpeg} show the different of JPEG and our method. JPEG image id generated by image quality level $3$, and thermal data of our method does $1390$ rounds of separate and compressed by Huffman Coding. In this case, Huffman Coding can reduce $39\%$ of compressed data size.
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								\begin{figure}[ht]
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									\begin{minipage}[b]{0.45\linewidth}
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										\centering
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								 		\includegraphics[width=\linewidth]{figures/my4000.png}
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										\caption{Data compressed by Proposed Method (4KB)}
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										\label{fig:4KMy}
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									\end{minipage}
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									\hspace{0.05\linewidth}
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									\begin{minipage}[b]{0.45\linewidth}
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										\centering
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								 		\includegraphics[width=\linewidth]{figures/quality3.jpg}
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										\caption{Data compressed by JPEG (4KB)}
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										\label{fig:4KJpeg}
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									\end{minipage}
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								\end{figure}
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								Figure~\ref{fig:compareToJpeg} shows that the size of file can reduce more than $50\%$ compared to JPEG image when both have $0.5\% (0.18^\circ C)$ of root-mean-square error. Our method has $82\%$ less error rate when the compressed data size is $4KB$. The percentage of file size is compared to PNG image. 
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								\begin{figure}[ht]
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									\centering
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								 	\includegraphics[width=\columnwidth]{figures/compareToJpeg.pdf}
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									\caption{Proposed method and JPEG comparing}
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									\label{fig:compareToJpeg}
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								\end{figure}
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								The computing time of a $480 \times 640$ thermal data on Raspberry Pi 3 is:
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								\subsubsection{Date Structure Initialize}
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								0.233997 second.
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								\subsubsection{Thermal Data Loading}
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								1.268126 second.
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								\subsubsection{Regions dividing}
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								About 4.6 microsecond per separation. Figure~\ref{fig:computeTime} shows the computation time of Region dividing.
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								Total time is about 1.5 second.
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								\begin{figure}[ht]
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									\centering
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								 	\includegraphics[width=\columnwidth]{figures/computeTime.pdf}
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									\caption{Computation Time of Regions Dividing}
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									\label{fig:computeTime}
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								\end{figure}
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