A Probabilistic Approach to Geometric Hashing using Line Features
A Probabilistic Approach to Geometric Hashing using Line Features
A Probabilistic Approach to Geometric Hashing using Line Features
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CHAPTER 3. NOISE IN THE HOUGH TRANSFORM 37<br />
Indeed, our experiments showed that most of the undetected lines are slanting lines with<br />
small slopes.<br />
While background subtraction works well <strong>to</strong> remove bias in favor of long line segments<br />
over short line segments, it in fact implicitly applies the principle of the-winner-takes-all. In<br />
particular, when a long line segment intersects a short line segment, their intersection pixel<br />
will be classiæed as belonging <strong>to</strong> the long line segment and subtracted from the image after<br />
the long line segment is detected. However, when these two line segments do not intersect<br />
each other even though their extended lines do, the perceptual grouping technique we use<br />
reduces this adverse eæect.<br />
In regard <strong>to</strong> accuracy, we observe that line length is the key role aæecting the accuracy<br />
of Hough transform results. The Hough transform works well <strong>to</strong> detect long line segments<br />
even if the image is quite noisy. As line length decreases, noise aæects the accuracy of the<br />
Hough transform even more seriously.<br />
When the center of a segment is far away from the projection of the origin on<strong>to</strong> the<br />
extended line of the segment, the average error of r increases. This phenomenon can be<br />
rationalized as follows èsee Figure 3.6è: Since our algorithm loops through ç, we in fact<br />
consider a line through the origin with slope angle ç èi.e., with line parameter èç +90 æ ; 0èè<br />
and project all the image edgels on<strong>to</strong> this line. If bucket èç; rè in Hough space is detected<br />
with n votes, roughly n edgels are projected on<strong>to</strong> the line at positions roughly r distant<br />
from the origin. With this viewpoint in mind, due <strong>to</strong> the quantization of images, if the<br />
center of a line segment, with line parameter èç; rè, is far away from the intersection point<br />
of line èç; rè and line èç +90 æ ; 0è, the projections èon<strong>to</strong> line èç +90 æ ; 0èè of the points of<br />
that line segment disperse èon line èç +90 æ ; 0èè around the position r distant from the<br />
origin èexcept when the orientation of the line segment is0 æ ,45 æ ,90 æ or 135 æ .è