jueves, 15 de noviembre de 2018

Ficha del recurso:


Vínculo original en MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8, 433-440 900-906; 10.4028/www.scientific.net/AMR.433-440.900 2012
Mamatha, HR; Srikanta, MK; Amrutha, KS; Anusha, P; Azeemunisa, R

Última actualización:

martes, 5 de junio de 2012

Entrada en el observatorio:

martes, 5 de junio de 2012



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Artificial Immune System Based Recognition of Handwritten Kannada Numerals

Artificial immune system (AIS) based classification approach is relatively new in the field of pattern recognition (PR). The capability of AIS for learning new information, recalling what has been learned and recognizing a decentralized pattern are reasons why numerous models have been developed, implemented and used in various types of problems. This paper explores this paradigm in the context of recognition of handwritten Kannada numerals. In this paper, the AIS is used for training the extracted features of handwritten Kannada numerals. Zonal based feature extraction algorithm is being used and K-Nearest Neighbor (K-NN) classifier is used for classification. The performance of the proposed algorithm has been investigated in detail on nearly 1250 samples of Handwritten Kannada Numerals and an recognition accuracy of 98.11% has been obtained.