GRAMMATICAL EVOLUTION FOR FEATURE EXTRACTION IN LOCAL THRESHOLDING PROBLEM
Keywords:
classification, ekstrak fitur, extract feature, feature, fitur, grammatical evolution, klasifikasi, local thresholding
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. Variasi intensitas pencahayaan pada citra dokumen akan menyebabkan kesulitan dalam menentukan nilai threshold dari citra tersebut. Pendekatan statistik konvensional tidak cukup baik dalam memecahkan masalah ini. Dalam hal ini, diperlukan nilai threshold yang berbeda-beda untuk setiap bagian citra. Nilai threshold dari setiap bagian citra dapat dipandang sebagai masalah klasifikasi. Dalam permasalahan klasifikasi semacam ini, dibutuhkan pencarian fitur-fitur terbaik. Di sini diusulkan sebuah pendekatan baru untuk mengekstrak fitur-fitur tersebut dengan menggunakan grammatical evolution. Nilai kebaikan dari masing-masing fitur akan dihitung secara saling lepas. Dalam percobaan yang dilakukan, tampak bahwa penggunaan fitur-fitur baru tersebut menghasilkan hasil yang sangat baik. Hanya ditemukan 5 kesalahan pengklasifikasian dalam 45 kasus.
Published
2012-07-29
How to Cite
Gunawan, G. F., Gosaria, S. C., & Arifin, A. Z. (2012). GRAMMATICAL EVOLUTION FOR FEATURE EXTRACTION IN LOCAL THRESHOLDING PROBLEM. Jurnal Ilmu Komputer Dan Informasi, 5(2), 106-111. https://doi.org/10.21609/jiki.v5i2.197
Section
Articles
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