The first test (\RefFig{fig:synth}) compares the performance of both detectors on a set of 1000 synthesized images containing 10 randomly placed input segments with random width between 1 and 4 pixels. Altough this perfect world context with low gradient noise tends to soften the old detector weaknesses, the results of \RefTab{tab:synth} show slightly better width and angle measurements on long segments for the new detector. The new detector generates more small segments that degrade the angle estimations, but it produces a smaller amount of false detections and succeeds in finding most of the input segments. \begin{figure}[h] %\center \begin{tabular}{ c@{\hspace{0.1cm}}c@{\hspace{0.1cm}}c@{\hspace{0.1cm}}c@{\hspace{0.1cm}}c} \includegraphics[width=0.19\textwidth]{Fig_synth/statsExample.png} & \includegraphics[width=0.19\textwidth]{Fig_synth/statsoldPoints.png} & \includegraphics[width=0.19\textwidth]{Fig_synth/statsoldBounds.png} & \includegraphics[width=0.19\textwidth]{Fig_synth/statsnewPoints.png} & \includegraphics[width=0.19\textwidth]{Fig_synth/statsnewBounds.png} \begin{picture}(1,1) \put(-310,0){a)} \put(-240,0){b)} \put(-170,0){c)} \put(-100,0){d)} \put(-30,0){e)} \end{picture} \end{tabular} \caption{Evaluation on synthesized images: a) one of the test images, b) output segments points from the old detector and c) their minimal digital straight segments, d) output segments points from the new detector and e) their minimal digital straight segments.} \label{fig:synth} \end{figure} \begin{table} \centering \input{Fig_synth/statsTable} \caption{Measured performance of both detectors on a set of synthesized images. $S$ is the set of all the input segments pixels, $D$ the set of all the detected segments pixels.} \label{tab:synth} \end{table}