Intelligent Recognition of Ancient Persian Cuneiform Characters

Abstract

This paper presents an intelligent character recognition system based on utilising a back propagation neural network model. The characters in question are unique and rare to be addressed in such applications. These are the ancient Persian Cuneiform alphanumerical characters. The recognition system comprises firstly, image processing phase where clear and noisy or degraded images of the ancient script are prepared for processing by the neural model in the second phase. The importance of such application lies in its potential to make translating ancient scripts and language easier, faster and more efficient. Experimental results indicate that our proposed method can be further applied successfully to other ancient languages and may be utilised in museums and similar environments.

Deep Aramaic: Towards a synthetic data paradigm enabling machine learning in epigraphy

“…Edan [17] classified Cuneiform signs using k-Nearest Neighbors on 1,500 examples. Mostofi and Khashman [18] experimented with shallow neural networks on 5,000 cases. Can et al [19] worked with 10,000 Maya glyphs.…”

Cuneiform Tablets Image Preprocessing Proposed Algorithms Techniques for Pattern Recognition

“…Hilal Yousif [1] proposed recognition method for cuneiform symbols depending on intensity curve features about the cuneiform symbols, and with same context. Fahimeh [5] presented recognition method of Persian cuneiform characters by neural network with back propagation model [6]. Raed presented a method for extract cuneiform symbols from clay tablets based on selected wavelate bases algorithm and with retrieving process.…”