We propose here a standardised protocol to record and trace painted inscriptions, in order to minimise personal biases DStretch®, a plug-in for ImageJ© specifically designed for the enhancement of digital images, allows reproducible and operator-independent results, improving objectivity in documenting rock art sites in remote and harsh environments We provide two examples of its application to Ẓufār sites in Oman, and compare our results with previously published tracings The improvement is so good that we envisage to apply the same method to a number of other sites, with a view to a reappraisal of the corpus of painted inscriptions of Ẓufār

https://scholarlypublications.universiteitleiden.nl/access/item%3A2716678/view

The Ẓufār painted Inscriptions in Oman : Epigraphy and New Technologies

Character recognition on inscriptions is an area which explores our knowledge of an ancient language. Inscriptions were done in all kinds of environments. This work focuses on recognizing Tamil language characters on stone-based images. From the inscription images, we come to know about the importance of old century languages. Some of the general challenges researchers face in recognizing the characters in stone inscriptions are differentiating the foreground pixel from the background stone images, perspective distortion, different light illumination, the same kind of background/foreground, damaged stones, lack of shape and size of the text. Despite the different ways proposed by the researchers, obstacles and issues continue to exist. This survey attempts to give a detailed analysis of the recent research works on character recognition from the images of stone inscriptions with a special reference to Tamil. It details the methods applied for preprocessing, feature extraction and classification. It gives a road map for future researchers who wish to carry out research in this area.

Ancient Tamil Character Recognition from Stone Inscriptions – A Theoretical Analysis

The ability to spot a few known characters or symbols allows the linguists and historians to guess the era in which an inscription was made. Manual spotting of these characters proves to be very laborious and error-prone. Hence, automation in character spotting has evolved in recent time, which has its own challenges due to natural wear and tear of inscriptions through aging. In this paper, we present a computationally efficient technique for character spotting using certain concepts from rough set theory. After image binarization, we compute various attributes for the isolated symbols within the ambit of rough set. In order to spot a symbol in the inscription, the corresponding attribute set for the query symbol is matched with that of the inscribed symbols. We provide the details of the method in this paper and show that the symbols or characters can be quite accurately spotted in the inscription.

A Novel Rough Set based Technique for Character Spotting on Inscription Images

Character recognition on inscriptions is an area which explores our knowledge of an ancient language. Inscriptions were done in all kinds of environments. This work focuses on recognizing Tamil language characters on stone-based images. From the inscription images, we come to know about the importance of old century languages. Some of the general challenges researchers face in recognizing the characters in stone inscriptions are differentiating the foreground pixel from the background stone images, perspective distortion, different light illumination, the same kind of background/foreground, damaged stones, lack of shape and size of the text. Despite the different ways proposed by the researchers, obstacles and issues continue to exist. This survey attempts to give a detailed analysis of the recent research works on character recognition from the images of stone inscriptions with a special reference to Tamil. It details the methods applied for preprocessing, feature extraction and classification. It gives a road map for future researchers who wish to carry out research in this area. 

Abstract Recent advances in image capturing and 3D scanning technologies along with their significant reduction in production costs have brought to the general public handheld devices equipped with several useful sensors and data collection instruments. This chapter discusses the mission of digitization projects and particularly the Digital Epigraphy and Archaeology Project (DEA) ( www.digitalepigraphy.org ) and its collection of 3D digitized material and applications of virtual and augmented reality alongside the Foucauldian notion of heterotopia and heterochrony. It argues that digital archaeology affords the users a transcendent understanding of the ancient and the modern world, as it enables them to move beyond themselves through virtuality while extending their perception via augmented reality and advanced physicality. Ultimately, the goal of the chapter is to contextualize epigraphy and archaeology within the concept of spatialization and open a discussion of the possibilities for “physical contact,” reappreciation of the concept of physicality, and study of digital artifacts. 

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“Please, Touch the Exhibits”: 3D Archaeology for Experiential Spatialisation

A novel interactive technique for extraction of text characters from the images of stone inscriptions is introduced in this paper. It is designed particularly for on-site processing of inscription images acquired at various historic palaces, monuments, and temples. Its underlying principle is made of several robust character-analytic elements like HoG features, vowel diacritics, and location-bounded scan lines. Since the process involves character spotting and extraction of the inscribed information to editable text, it would subsequently help the archaeologists for epigraphy, transliteration, and translation of rock inscriptions, particularly for the ones having high degradations, noise, and a variety of styles according to the mason origin and reign. The spotted characters can also be used to create a database for ancient script analysis and related archaeological work. We have tested our method on various stone inscriptions collected from some of the heritage sites of Karnataka, India, and the results are quite promising. An Android application of the proposed work is also developed to aid the epigraphers in the study of inscriptions using a tablet or a mobile phone.

Ananth Nath Talla

Papers

A Method for Extracting Text from Stone Inscriptions Using Character Spotting