Article: multi-line selection

Article/method.tex

@@ -227,14 +227,19 @@ This strategy provides a first quick analysis of the local context before
 extracting the segment and contributes to notably stabilize the overall
 process.
 
-When selecting candidates for the fine detection stage, an option is left
-to also reject points with a gradient vector in an opposite direction to
-the gradient vector of the blurred segment start point.
-In that case, called {\it edge selection mode}, all the blurred segment
-points have the same direction.
-If they are not rejected, points with opposite gradients are aggregated
-into a same blurred segment, allowing the detection of the two opposite
-edges of a thin straight object. This is called {\it line selection mode}.
+When selecting candidates for the fine detection stage, an option, called
+{\it edge selection mode}, is left to filter the points according to their
+gradient direction.
+In {\it main edge selection mode}, only the points with a gradient vector
+in the same direction as the start point gradient vector are added to the
+blurred segment.
+In {\it opposite edge selection mode}, only the points with an opposite
+gradient vector direction are kept.
+In {\it line selection mode} this filter is not applied, and all the
+candidate points are aggregated into a same blurred segment, whatever the
+direction of their gradient vector.
+This mode allows the detection of the two opposite edges of a thin straight
+object.
 This distinction is illustrated on \RefFig{fig:edgeDir}.
 
 \begin{figure}[h]
@@ -285,10 +290,8 @@ blurred segment extension in the fine tracking step.
 Multiple detections of the same edge are thus avoided.
 
 In edge selection mode (\RefFig{fig:edgeDir} b), the multi-detection
-algorithm is executed twice.
-In the second run, the start point is rejected and only candidate points
-with opposite gradient direction are considered to extend the blurred
-segment.
+algorithm is executed twice, first in main edge selection mode, then
+in opposite edge selection mode.
 
 %Beyond the possible detection of a large set of edges at once, the
 %multi-detection allows the detection of some unaccessible edges in