Jaap Oosterbroek - Using Max-Trees with alternative connectivity classes in historical document processing
In mathematical morphology, connectivity classes are a formal way of describing the grouping of sets of elements in a graph. When applied to images, connectivity classes can easily be used to describe relations in binary images and generalizes to gray-scale by means of threshold super-positioning. Connectivity classes have long been of interest in image processing research, because they provided a basis for the invention and verification of connectivity based algorithms. Much work has been invested in finding structured ways of modifying connectivity classes with predictable results. Here we present a method of using a combination of two known types of connectivity: mask and edge-based connectivity, in historical document processing. Max-Trees are data structures that can be used to express various connectivity classes. A system was build that uses a Max-Tree for all steps in the document processing chain, from preprocessing to feature generation. The system aims to show that a combination of these two types of connectivity counteracts some of their mutual weaknesses. Two types of filters: the k-subtractive and k-absorption filters were used to remove noise and help with segmentation. Finally a class of features that can efficiently be computed in a Max-Tree, Normalized Central Moments, were used to classify the character zones resulting from this segmentation.
Laatst gewijzigd: | 13 juni 2019 13:40 |
Meer nieuws
-
10 juli 2025
Nationale Wetenschapsagenda subsidie voor nanomedicine onderzoek
Prof. Dr. Anna Salvati, Dr. Christoffer Åberg en Prof. Dr. Siewert-Jan Marrink ontvangen een Nationale Wetenschapsagenda financiering om met het NanoMedNL consortium levensreddende medicijnen op basis van nanotechnologie verder te ontwikkelen.
-
07 juli 2025
Masterstudent Industrial Engineering and Management Ana Lazar wint GUF-100 prijs
Tijdens de RUG Ceremony of Merits op 4 juli is Ana Lazar uitgeroepen tot winnaar van de GUF-100 prijs en daarmee tot de beste student van de Faculty of Science and Engineering 2024-2025.
-
03 juli 2025
Erik Heeres ontvangt RUG Impact Innovator Excellence Award
Tijdens de RUG Ventures Innovation Day heeft Prof. dr. ir. Erik Heeres van de Faculty of Science and Engineering (RUG) de Impact Innovator Excellence Award ontvangen.