GRAMMATICAL EVOLUTION FOR FEATURE EXTRACTION IN LOCAL THRESHOLDING PROBLEM

Abstract: The various lighting intensity in a document image causes diffculty to threshold the image. The conventional statistic approach is not robust to solve such a problem. There should be different threshold value for each part of the image. The threshold value of each image part can be looked as classifcation problem. In such a classifcation problem, it is needed to find the best features. This paper propose a new approach of how to use grammatical evolution to extract those features. In the proposed method, the goodness of each feature is calculated independently. The best features then used for classification task instead of original features. In our experiment, the usage of the new features produce a very good result, since there are only 5 miss-classification of 45 cases.

Keywords: classification; ekstrak fitur; extract feature; feature, fitur; grammatical evolution; klasifikasi; local thresholding

Author: Go Frendi Gunawan, Sonny Christiano Gosaria, Agus Zainal Arifin

Journal Code: jptkomputergg120018

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