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- \section{Performance Evaluation}
- \label{sec:eval}
-
- To evaluate the effectiveness of the proposed method, we do the different ratios of compressing on a thermal image by our method compare 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 image size is $480 \times 640$ pixels. The JPEG image is generated by OpenCV $3.3.0$, and image quality from $1$ to $99$.
-
- 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 image of our method does $1390$ rounds of separate and compressed by Huffman Coding. In this case, Huffman Coding can reduce $39\%$ of our image size.
-
- \begin{figure}[ht]
- \centering
- \includegraphics[width=0.6\columnwidth]{figures/my4000.png}
- \caption{4KB Image by Proposed Method}
- \label{fig:4KMy}
- \end{figure}
-
- \begin{figure}[ht]
- \centering
- \includegraphics[width=0.6\columnwidth]{figures/quality3.jpg}
- \caption{4KB Image by JPEG}
- \label{fig:4KJpeg}
- \end{figure}
-
- Figure~\ref{fig:compareToJpeg} shows that the size of file can reduce more than $50\%$ compare 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 both size are $4KB$ image. The percentage of file size is compare to PNG image.
-
- \begin{figure}[ht]
- \centering
- \includegraphics[width=\columnwidth]{figures/compareToJpeg.pdf}
- \caption{Proposed method and JPEG comparing}
- \label{fig:compareToJpeg}
- \end{figure}
-
- The computing time on Raspberry Pi 3 is:
- \subsubsection{Date Structure Initialize}
- XXX.XXX second.
- \subsubsection{Image Loading}
- XXX.XXX second.
- \subsubsection{Region Separation}
- XXX.XXX second. (a chart)
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