Indian scripts

The exhibition “History of Indic Scripts”, produced in the framework of the E-QUAL Project, was inaugurated on 9 June 2016 in Palazzo Poggi, University of Bologna. The exhibition consisted of 15 panels with text and pictures (design and development by Marco Franceschini).

The present study offers an introductory survey on the history of Indic scripts. It was prepared in the frame of the E-QUAL project, and it provided the narrative structure on which a Moodle module on the same topic was built by the present author. Basically, it focuses on the developments of the Indic scripts, from the time of their earliest available attestations up to the time when the major present-day (modern) scripts reached their current form. The study is organized in six chapters. The first chapter has a prefatory character, in that it offers a general contextualization of what will be covered in the following sections of the work: the general plan of the work is outlined, the basic concepts are defined, and the major phenomena connected with the history of the Indic scripts are presented. In chapters two through six, a chronological account of the development of the Indic scripts is given, from their earliest attestations up to their current form. Chapter six is followed by three additional sections (Appendices), each focusing on a specific topic, i.e. the languages used in Indian inscriptions, the Siddhamātṛkā script, and the typological classification of the Indic scripts.

Online Handwriting Recognition has been a rigorous research area for the last few decades. Substantial amount of work has been reported on the online handwriting recognition of Western, Chinese, Japanese, Korean and Arabic Scripts, but few related to Indian scripts. In this paper a review of online HCR work on almost all popular Indian scripts such as Devanagari, Gurmukhi, Bangla, Tamil, Telugu, Malayalam, Urdu, Kannada, Oriya, and Gujarati is presented. The review is organized into 7 sections. Section 1 covers introduction. Properties of Indian scripts and general architecture of online HCR is given in section 2 and 3. In section 4, research work done on online handwriting for Indian scripts is summarized. Challenges of online HCR are discussed in section 5. The scope of future work and further steps needed for Indian script based online HCR development are discussed in section 6. Conclusions are given in section 7.

　　The Siddham Script derives from the north Indian script used from the sixth through the tenth centuries. It was introduced to East Asia along with Buddhism. Zhiguang, an eighth-century Chinese monk, wrote the highly regarded Xitan zi ji (悉曇字記, “An Explanation of Siddham Letters”) to explain Siddham spelling and pronunciation. However, the forms of the letters representing the initial long ī, cha, and ḍha in the Xitan zi ji are different from those used in northern India. According to textual research on Siddham learning in Tang China, the causes and background of the use of these three forms are considered to be as follows.
　  This article points out that the letter for the initial long ī in the Xitan zi ji is a letter for the initial short i in northern India and represents the short i in the old Siddham manuscripts. This letter was regarded as the initial long ī in the Xitan zi ji owing to a curious type of Siddham syllabary or to a misunderstanding that arose in Siddham learning in China.
　  The letter for cha is written as ccha in the Xitan zi ji. This could be because the letter for cch was regarded in a particular branch of the Siddham tradition in China as a variant form of ch based on Indian orthographical conventions for Buddhist manuscripts in Sanskrit.
　　One scholarly opinion is that the form of the letter of ḍha in the Xitan zi ji is erroneous. Presently, this issue continues to remain unresolved. At least it has been used in Tang China because it appears in some Siddham manuscripts.
  　Furthermore, this article points out that the forms of these three letters that appear in earlier manuscripts of Japanese Siddham studies that quote from the Xitan zi ji sometimes differ from those appearing in the extant Xitan zi ji manuscripts. This indicates that there once were versions of the Xitan zi ji that differ from the received version.
　  This article reveals that these three forms were used in Tang China, and that forms of Siddham script can be one of the important clues for studying manuscripts of Siddham studies.

The paper aims to highlight the religious interaction between the Buddhists in Srilanka and India in 9th century A.D. as gleaned from an inscription found from Ghuriyavan, Gaya district, Bihar. The inscription is written in Sanskrit language and Siddhamatrika characters.

Online Handwriting Recognition has been a rigorous research area for the last few decades. Substantial amount of work has been reported on the online handwriting recognition of Western, Chinese, Japanese, Korean and Arabic Scripts, but few related to Indian scripts. In this paper a review of online HCR work on almost all popular Indian scripts such as Devanagari, Gurmukhi, Bangla, Tamil, Telugu, Malayalam, Urdu, Kannada, Oriya, and Gujarati is presented. The review is organized into 7 sections. Section 1 covers introduction. Properties of Indian scripts and general architecture of online HCR is given in section 2 and 3. In section 4, research work done on online handwriting for Indian scripts is summarized. Challenges of online HCR are discussed in section 5. The scope of future work and further steps needed for Indian script based online HCR development are discussed in section 6. Conclusions are given in section 7.

In this paper a script independent automatic numeral recognition system is proposed. A single algorithm is proposed for recognition of Kannada, Telugu and Devanagari handwritten numerals. In general the number of classes for numeral recognition system for a scripts/language is 10. Here, three scripts are considered for numeral recognition forming 30 classes. In the proposed method 30 classes have been reduced to 18 classes. The global and local structural features like directional density estimation, water reservoirs, maximum profile distances and fill hole density are extracted. A Probabilistic neural network (PNN) classifier is used in the recognition system. The algorithms efficiency is for various radial values of PNN classifiers, with different experimental setup and obtained encouraging results are compared to other methods proposed in the literature survey. A total of 2550 numeral images of Kannada, Telugu and Devanagari scripts are considered for experimentation. The overall...