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
