Abstract
The trace transform allows one to construct an unlimited number of image features that are invariant to a chosen group of image transformations. Object signature that is in the form of string of numbers is one kind of the transform features. In this paper, we demonstrate a wrapper method along with several ranking evaluation measurements to select useful features for the recognition of handwritten Jawi images. We compare the result of the recognition with those obtained by using methods where features are randomly selected or no feature selection at all. The proposed methods seem to be most promising.
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Nasrudin, M.F., Omar, K., Liong, CY., Zakaria, M.S. (2010). Object Signature Features Selection for Handwritten Jawi Recognition. In: de Leon F. de Carvalho, A.P., RodrÃguez-González, S., De Paz Santana, J.F., RodrÃguez, J.M.C. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14883-5_88
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DOI: https://doi.org/10.1007/978-3-642-14883-5_88
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