Choosing Shape Features by means of Genetic Algorithms for Gylph-clustering of Historical Documents | Zendy

Jan-Hendrik Worch | Zendy; Bj ̈orn Gottfried | Zendy

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Choosing Shape Features by means of Genetic Algorithms for Gylph-clustering of Historical Documents

Author(s) -

Jan-Hendrik Worch,

Bj ̈orn Gottfried

Publication year - 2014

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/17792-8585

Subject(s) - computer science , glyph (data visualization) , cluster analysis , selection (genetic algorithm) , task (project management) , set (abstract data type) , field (mathematics) , data mining , genetic algorithm , process (computing) , artificial intelligence , feature selection , feature (linguistics) , pattern recognition (psychology) , information retrieval , algorithm , machine learning , visualization , linguistics , philosophy , mathematics , management , pure mathematics , economics , programming language , operating system

The solution for a feature selection problem is presented in the field of document image processing. The choice of shape features for describing glyphs of historical documents is a non-trivial task since the variations of glyphs in different documents is innumerable. Hence, the manual selection of shape features would be a cumbersome task. To select a subset of features from a given set a genetic algorithm is used which optimises the result of a clustering process by x-means. The result of x-means is evaluated by using different quality measures. The optimisation methodology is illustrated within a case study, in which the selection of an appropriate set of features is a crucial part of the system. The intended application supports a user who is transcribing historical documents by showing him similar occurrences of a given glyph.

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