# Full text: Proceedings International Workshop on Mobile Mapping Technology

```shared with other nonparallel lines. For those selected segments,
after line following, each segment consists of discrete points
(jc f ,) (/ = 0 ,— ,n). These points are fitted to a straight line with
two parameters a and b
y=a+bx (12)
where
V
Suppose two parallel projected lines have parameters (a,b) and
(a ,b ) respectively, the vanishing point should have coordinates
A =U -aj)/[bj -b)
X. =X —ap)l{^ J -b) ( 13 )
So another fitted line with parameters (a k ,b k ) is parallel to these
two lines if and only if
\cb + xh~y\^ £ (14)
where £ >0 is relative to the data precisioin.
Figures 9(a) to (d) are parallel line grouping results through
perspective geometry.
(c) (d)
Figure 9. Extracted parallel lines
To extract roads in a mobile mapping imagery sequence, a set of
road line seeds are defined, which have the lowest level of slopes
and are parallel to each other in the object space. Among the seed
edges in the image space, those pairs share the same vanishing
point and have the anti-parallel character (the difference between
direction angles is less than K but larger than K / 2 , caused by
edge candidates. The nearest end points of the edge candidates
are then connected with a constraint on direction angles.
Knowing the camera position in the image space with the help of
GPS/INS data, the initial curb/lane lines are delineated through
conditional dilation within the segmented image. Edges nearby
the lines are selected if their lengths are longer than a specified
threshold. These edges constitute a geometric constraint used to
select the preliminary line candidates (Figures 10).
/ -f
'X
(a) (b)
> -j
c, *
(c) (d)
Figure 10. Preliminary road line candidates
The candidates are then refined through a parallel line grouping
process and become those improved in Figures 11.
X
¡X
XX
(a) (b)
XX
XX
(c) (d)
6. ABOVEGROUND OBJECTS EXTRACTION AND
CLASSIFICATION
Shadow is an important feature in aerial imagery. In principle,
using shadows, date, time, and orientation of the image, the sun’s
position can be determined. Inversely, artificial shadows of
known objects can be generated for object recognition purposes.
In photo interpretation, the combination of an object surface (for
example, a building roof) and its shadow make them
distinguished from others. After image segmentation, statistic
properties such as mean and variance are calculated in each
segmented area. One area (shadow) has a very low intensity mean
and the adjacent area (its corresponding object) may have a very