Download PDF by David Peleg (auth.), Rossella Petreschi, Giuseppe Persiano,: Algorithms and Complexity: 5th Italian Conference, CIAC

By David Peleg (auth.), Rossella Petreschi, Giuseppe Persiano, Riccardo Silvestri (eds.)

ISBN-10: 3540401768

ISBN-13: 9783540401766

ISBN-10: 3540448497

ISBN-13: 9783540448495

This ebook constitutes the refereed court cases of the fifth Italian convention on Algorithms and Computation, CIAC 2003, held in Rome, Italy in may well 2003.

The 23 revised complete papers offered have been conscientiously reviewed and chosen from fifty seven submissions. one of the issues addressed are complexity, complexity concept, geometric computing, matching, on-line algorithms, combinatorial optimization, computational graph thought, approximation algorithms, community algorithms, routing, and scheduling.

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Extra resources for Algorithms and Complexity: 5th Italian Conference, CIAC 2003, Rome, Italy, May 28–30, 2003. Proceedings

Example text

We anchor the line segment q1 q2 with the line segment pi pj with q1 anchored at pi , (if it fails we would anchor q2 with pi ) and search in Si (data structure corresponding to pi in S) to identify the presence of a match. For each point qα ∈ Q, the tuple ( qα q1 q2 , δ(q1 qα )) is searched in Si . , the triangle ∆p pi pj in P is congruent with the triangle ∆qα q1 q2 in Q), p matches with qα . If all the points in Q are matched with k points of P , then Q matches with P (see Figure 1 for an illustration).

The time reported is averaged over a number of experiments for different values of K. The drastic improvement in the execution time, as reported in the last column of Table 1, is due to the fact that, in general, the maximum An Improved Algorithm for Point Set Pattern Matching under Rigid Motion 41 Table 1. Comparative results with respect to CPU Time CPU Time in µ sec. 35 number of equidistant pair of points is very small compared to its theoretical upper bound (see Table 2). Table 2. 2 Experiment with Real Fingerprint Minutiae The proposed algorithm is also tested using real fingerprint minutiae, extracted from fingerprints in the NIST 14 sdb [10,26].

1 Preprocessing The T data structure for this problem is an AVL-tree containing the length of the line segments in the sample set P . The members in T are all distinct. If more than one line segment are of the same length δ, then they are stored in the structure χδ attached to the corresponding node of T . Each entry of χδ corresponds to a line segment = pi pm ∈ P ; it contains a 4-tuple {pi , pm , ptr1 , ptr2 }, where ptr1 and ptr2 point to two AVL-trees Si and Sm corresponding to the points pi and pm respectively.

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Algorithms and Complexity: 5th Italian Conference, CIAC 2003, Rome, Italy, May 28–30, 2003. Proceedings by David Peleg (auth.), Rossella Petreschi, Giuseppe Persiano, Riccardo Silvestri (eds.)


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