Texture Detection for Letter Carving Segmentation of Ancient Copper Inscriptions

Author:

Rasmana Susijanto T.12,Suprapto Yoyon K.1,Purnama I. Ketut Eddy1,Uchimura Keiichi3,Koutaki Gou3

Affiliation:

1. Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Keputih – Sukolilo, Surabaya 60111, East Java, Indonesia

2. Computer Engineering, Institut Bisnis dan Informatika Stikom Surabaya, Jl. Raya Kedung Baruk 98 Surabaya 60298, East Java, Indonesia

3. Graduate School of Science and Technology, Kumamoto University, 2-40-1 Kurokami Chuo-ku, Kumamoto City, 860-8555, Japan

Abstract

As relics of history, ancient copper inscriptions are found in many countries. Information in the image or letter forms contained on copper ancient inscription has a very high value. The age and environmental factors caused damage to the surface of the inscription and also reduced the appearances of the image and letter. In this paper, we describe a novel segmentation methodology based on multi-texture features for ancient copper inscriptions which were severely damaged. The segmentation results of letters on ancient copper inscriptions by using the proposed method have an average accuracy of 90%. Based on these results, the proposed method is suitable for letter segmentation of the ancient copper inscriptions.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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