Adaptive binarization method for enhancing ancient malay manuscript images

Authors:
Sitti Rachmawati Yahya;Siti Norul Huda Sheikh Abdullah;Khairuddin Omar;Choong-Yeun Liong
Affiliations:
Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia;Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia;Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia;School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
Venue:
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Year:
2011

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Abstract

In order to transform ancient Malay manuscript images to be cleaner and more readable, enhancement must be performed as the images have different qualities due to uneven background, ink bleed, or ink bleed and expansion of spots. The proposed method for image improvement in this experiment consists of several stages, which are Local Adaptive Equalization, Image Intensity Values, K-Means Clustering, Adaptive Thresholding, and Median Filtering. The proposed method produces an adaptive binarization image. We tested the proposed method on eleven ancient Malay manuscript images. The proposed method has the smallest average value of Relative Foreground Area Error compared to the other state of the art methods. At the same time, the proposed method have produced the better results and better readability compared to the other methods.