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ALGORITHM TO CALCULATE THE HAUSDORFF DISTANCE ON SETS OF POINTS REPRESENTED BY K2-TREE

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dc.creatorMIGUEL ESTEBAN ROMERO VÁSQUEZ
dc.creatorGILBERTO ANTONIO GUTIÉRREZ RETAMAL
dc.date2019
dc.date.accessioned2025-01-10T15:06:39Z
dc.date.available2025-01-10T15:06:39Z
dc.date.issued2019
dc.description.abstractTHE HAUSDORFF DISTANCE BETWEEN TWO SETS OF POINTS A AND B CORRESPONDS TO THE LARGEST OF THE DISTANCES BETWEEN EACH OBJECT X ? A AND ITS NEAREST NEIGHBOR IN B. THE HAUSDORFF DISTANCE HAS SEVERAL APPLICATIONS, SUCH AS COMPARING MEDICAL IMAGES OR COMPARING TWO TRANSPORT ROUTES. THERE ARE DIFFERENT ALGORITHMS TO COMPUTE THE HAUSDORFF DISTANCE, SOME OPERATE WITH THE SETS OF POINTS IN MAIN MEMORY AND OTHERS IN SECONDARY MEMORY. ON THE OTHER HAND, TO FACE THE CHALLENGE OF INDEXING LARGE SETS OF POINTS IN MAIN MEMORY, THERE ARE COMPACT DATA STRUCTURES SUCH AS K 2 -TREE WHICH, BY MINIMIZING STORAGE, CAN BE EFFICIENTLY CONSULTED. AN EFFICIENT ALGORITHM (HDK2) THAT ALLOWS THE CALCULATION OF THE HAUSDORFF DISTANCE IN THE COMPACT STRUCTURE K 2 -TREE IS PRESENTED IN THIS ARTICLE. THIS ALGORITHM ACHIEVES AN EFFICIENT SOLUTION IN BOTH TIME AND SPACE. THROUGH A SERIES OF EXPERIMENTS, THE PERFORMANCE OF OUR ALGORITHM WAS EVALUATED TOGETHER WITH OTHERS PROPOSED IN LITERATURE UNDER SIMILAR CONDITIONS. THE RESULTS ALLOW TO CONCLUDE THAT HDK2 HAS A BETTER PERFORMANCE IN RUNTIME THAN SUCH ALGORITHMS
dc.formatapplication/pdf
dc.identifier.doi10.1109/CLEI.201800064
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/10468
dc.languagespa
dc.publisherAMERICAN COMPUTER CONFERENCE
dc.relation.uri10.1109/CLEI.201800064
dc.rightsPUBLICADA
dc.titleALGORITHM TO CALCULATE THE HAUSDORFF DISTANCE ON SETS OF POINTS REPRESENTED BY K2-TREE
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE CIENCIAS DE LA COMPUTACION Y TECNOLOGIA DE LA INFORMACION.
ubb.Otra ReparticionDEPARTAMENTO DE CIENCIAS DE LA COMPUTACION Y TECNOLOGIA DE LA INFORMACION.
ubb.SedeCHILLÁN
ubb.SedeCHILLÁN
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