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Memetic Computing
Erschienen in: Memetic Computing 1/2015

01.03.2015 | Regular Research Paper

Recognition of archaic Lanna handwritten manuscripts using a hybrid bio-inspired algorithm

verfasst von: Arit Thammano, Sakkayaphop Pravesjit

Erschienen in: Memetic Computing | Ausgabe 1/2015

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Abstract

This paper proposes a new character recognition system for archaic Lanna handwritten characters. The proposed system consists of two main processes: the segmentation process and the recognition process. The segmentation process decomposes the touching or overlapping characters, commonly found in Lanna manuscripts, into isolated characters. In the recognition process, the proposed system uses the self-organizing map to divide the input images into several clusters. The clonal selection algorithm of the artificial immune system is then used to build a recognition model for each cluster created by the self-organizing map. Finally, the particle swarm optimization is employed as a local search mechanism. The proposed system was evaluated and compared to several state-of-the-art approaches. The experimental results demonstrate that the proposed system is very effective in recognizing not only Lanna characters but also the handwritten numerals of the five most popular scripts.
Vorheriger Artikel Thematic issue on hybrid nature-inspired algorithms: concepts, analysis and applications
Nächster Artikel Group based Swarm evolution algorithm (GSEA) driven mental task classifier

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Metadaten
Titel
Recognition of archaic Lanna handwritten manuscripts using a hybrid bio-inspired algorithm
verfasst von
Arit Thammano
Sakkayaphop Pravesjit
Publikationsdatum
01.03.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Memetic Computing / Ausgabe 1/2015
Print ISSN: 1865-9284
Elektronische ISSN: 1865-9292
DOI
https://doi.org/10.1007/s12293-015-0152-3

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