Answers corrected

Methode/answerToReview.tex

@@ -145,7 +145,8 @@ despite Section 3.5 is allocated for explanation of it?
 We confirm that the performance results are obtained using the unsupervised
 mode.
 However, as the unsupervised algorithm is based on the supervised multiple
-line detection algorithm, these results {\bf also affect} the supervised detection.
+line detection algorithm, these results {\bf also reflect} the supervised
+detection performance.
 Furthermore, the supervised mode deals mainly with an interactive aspect,
 which was largely discussed in the former paper.
 In this context, there is a lack of available ground truth directly
@@ -169,14 +170,15 @@ the justification of selection of these initial parameter values should be
 presented and performance related to selection of this parameter value
 should also be presented and discussed.
 \begin{answer}
-Experiments on synthetic images aims at assessing the improved performance
+Experiments on synthetic images aim at assessing the improved performance
 beween formal and actual versions of the detector, including the thickness
 value estimation. The synthesized images are generated with a thickness
 varying from 2 up to 5 pixels.
 Therefore the initial assigned thickness is set to a greater value : 7. \\
 The other detectors aim at providing thin lines and may reject too
 scattered image lines. To adapt to this behavior, we retrict the detection
-to thin lines using the initial assigned thickness to 3 pixels.
+to thin lines using the initial assigned thickness to 3 pixels. \\
+The text of the paper has been precised accordingly.
 \begin{todo}
 Done.
 \end{todo}
@@ -188,11 +190,12 @@ method [11] at the York Urban dataset, in Table 2 and Fig. 5.
 Unfortunately, we have no more left space to extend Fig. 5, where images
 are already quite small.
 It would maybe be possible to add one line in the table, but the interest is
-weak if the the associated image is not displayed. \\
-We have added all these informations in the github, with the completed table.
-We just point out that achieved values have less meaning, because as explained
+weak in lack of the associated image. \\
+We have added all the required informations in the github, with the completed
+table.
+We notice that achieved values have less meaning here, because as explained
 in the paper, the lines detected by the former method are more likely to
-incorporate spurious points that artificially improve the width and length
+incorporate spurious points, that artificially grow the width and length
 values.
 \begin{todo}
 Ajouter les images et la ligne dans le github.