By Rafael Grompone von Gioi
The trustworthy detection of low-level photograph constructions is an previous and nonetheless difficult challenge in computing device imaginative and prescient. This e-book leads an in depth journey throughout the LSD set of rules, a line section detector designed to be absolutely automated. in keeping with the a contrario framework, the set of rules works successfully with no the necessity of any parameter tuning. The layout standards are completely defined and the algorithm's reliable and undesirable effects are illustrated on actual and artificial photographs. the problems concerned, in addition to the concepts used, are universal to many geometrical constitution detection difficulties and a few attainable extensions are discussed.
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Additional resources for A Contrario Line Segment Detection
Then, all its aligned pixels are excluded from being used by the remaining candidates, whose NFA values are re-computed without using them. Redundant detections share most of their aligned pixels. Thus, when the best candidate appropriates its pixels, it leaves few or no aligned pixels on redundant line segments; the new NFA values are large and the redundant line segments are no longer meaningful. 11 shows an example. Unfortunately, the previous approach does not solve all the problems. When two or more aligned line segments are present, see Fig.
2. 3. 4. 5. Try finer precisions, Try to reduce width, Try to reduce one side of the rectangle, Try to reduce the other side of the rectangle, Try even finer precisions. If a meaningful rectangle is found (NFA ≤ ε ), the improvement routine will stop after the step that found it. Step 1 tries the following precision values: p/2, p/4, p/8, p/16, and p/32, where p is the initial precision value. The value that produces the best NFA (the smallest) value is kept. 5 pixels. 5, where W is the initial width value.
Among the continuous formulations, the additive criterion seems to capture slightly finer details. 6 Exclusion Principle and Further Improvements As illustrated in Fig. 5, an exhaustive search for line segments produces many redundant detections. Two divergent approaches were proposed to cope with redundancy and inaccuracy. The first one uses a criterion to select the best detections and remove the others; this is done after the exhaustive search and validation. The second one uses the heuristic search plus validation strategy where a reduced number of candidates is selected previously to validation.
A Contrario Line Segment Detection by Rafael Grompone von Gioi