DOCSLIB.ORG

Devanagari and Gurmukhi Handwritten Character Generation Using Generative Adversarial Networks

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Devanagari and Gurmukhi Handwritten Character Generation Using Generative Adversarial Networks Devanagari and Gurmukhi Handwritten Character Generation using Generative Adversarial Networks Thesis submitted in partial fulfillment of the requirements for the award of degree of Master of Engineering in Computer Science and Engineering Submitted By Simerpreet Kaur (Roll No. 801632048) Under the supervision of: Dr. Karun Verma Assistant Professor, CSE Department COMPUTER SCIENCE AND ENGINEERING DEPARTMENT THAPAR INSTITUTE OF ENGINEERING AND TECHNOLOGY PATIALA – 147004 June 2018 i ACKNOWLEDGEMENT I would like to express my grateful thanks to my supervisor Dr. Karun Verma. This work would not have been possible without his encouragement and guidance. I thank my supervisor for his time, patience, discussion and valuable comments. His enthusiasm and optimism made this experience both rewarding and enjoyable. I am equally grateful to Dr. Maninder Singh, Professor and Head of Computer Science and Engineering Department, an excellent teacher and a well-credited researcher, who always encouraged us to keep going with the work. I will be failing in my duty if I don’t express my gratitude to Dr. S.S. Bhatia, Senior Professor and Dean of Academic Affairs, Thapar Institute of Engineering and Technology, for making all the provisions of infrastructure such as library facilities, computer labs equipped with net facilities, immensely useful for learners to equip themselves with latest in the field. I am also thankful to entire faculty and staff members of Computer Science and Engineering Department for their direct-indirect help and cooperation, which made my stay at Thapar Institute of Engineering and Technology memorable. Date: June, 2018 (Simerpreet Kaur) Place: Thapar Institute of Engineering and Technology ii ABSTRACT Today, computers have influenced the life of human beings to a great extent. The theory that computers can learn without being programmed to perform a specific task, have attracted the researchers to see if computers could learn from data. As deep learning became popular, the need for huge amounts of data has risen. The major problem faced in the area of deep learning is the data availability. In this dissertation, a generative technique is used to generate the handwritten Gurmukhi and Devanagari characters. This dissertation describes the implementation of handwritten Gurmukhi and Devanagari characters using deep learning technique named as Generative Adversarial Networks. Gurmukhi and Devanagari script is chosen for this research work as it is used directly or indirectly by more than 500 million people in the Indian subcontinent and less work is done on Devanagari and Gurmukhi script as compared to work done on other scripts such as English and Chinese. GANs are chosen for the implementation as it is proven to be the very powerful generative method. Here, we use 3-layer CNN having stride value of 2 for the feature extraction of handwritten character. The characters generated look like the character in the original dataset. Also by increasing the number of epochs the images are more recognizable and clear as well as the loss starts decreasing. iii TABLE OF CONTENTS CERTIFICATE .............................................................................................................. i ACKNOWLDEGEMENT............................................................................................ ii ABSTRACT .................................................................................................................. iii LIST OF FIGURES .................................................................................................... vii LIST OF TABLES ..................................................................................................... viii ABBREVIATIONS ...................................................................................................... ix Chapter 1: Introduction ............................................................................................... 1 1.1. Artificial Neural Networks ....................................................................... 3 1.1.1. Back Propagation ........................................................................... 4 1.2. Convolutional Neural Network ................................................................ 5 1.2.1. Convolutional Layer ..................................................................... 5 1.2.2. Pooling Layer ............................................................................... 6 1.2.3. Fully-Connected Layer ................................................................. 7 1.2.4. Activation Layer. .......................................................................... 7 1.2.5. Dropout Layer ............................................................................. 10 1.2.6. Batch Normalization ................................................................... 10 1.2.7. Loss Function ............................................................................. 11 1.3. Generative modeling ............................................................................... 11 1.3.1. Generative model working ......................................................... 12 1.4. Generative adversarial network .............................................................. 13 1.4.1. Adversarial loss .......................................................................... 13 1.5. Deep Convolutional Generative Adversarial Network ........................... 14 1.5.1 Architecture of DCGAN ............................................................. 14 1.6. Dissertation Outline ................................................................................ 15 Chapter 2: Literature Review .................................................................................... 16 Chapter 3: Problem Statement .................................................................................. 23 3.1 Problem Formulation ............................................................................... 23 3.2 Research Gap ........................................................................................... 24 3.3 Research Objectives ................................................................................. 24 iv Chapter 4: Gurmukhi and Devanagari Script Overview..……………………………...25 4.1. Gurmukhi Script ...................................................................................... 25 4.1.1. Overview ...................................................................................... 25 4.1.2. Gurmukhi consonants identifiers ................................................. 26 4.2. Devanagari Script ................................................................................... 26 4.2.1. Overview ...................................................................................... 26 4.2.2. Devanagari consonants and digits identifiers .............................. 27 Chapter 5: Implementation ................................................................................................ 28 5.1. Data Collection ........................................................................................ 28 5.2. Preprocessing ........................................................................................... 29 5.3. GANs Network Building ......................................................................... 30 5.3.1. Generator Network....................................................................... 31 5.3.2. Discriminator Network ................................................................ 32 5.3.3. Loss Calculation........................................................................... 33 5.3.4. Optimizer ..................................................................................... 34 5.3.5. Running Training Session ............................................................ 34 5.4. Output Generation .................................................................................... 34 Chapter 6: Results and Discussion .................................................................................... 35 6.1. Experiment 1 ............................................................................................ 35 6.2. Experiment 2 ............................................................................................ 42 Chapter 7: Conclusion and Future Scope ......................................................................... 50 7.1. Conclusion ................................................................................................ 50 7.3. Future Scope ............................................................................................ 50 Publications. ........................................................................................................................ 52 References ............................................................................................................................ 53 v LIST OF FIGURES Figure No. Title of Figure Page No. Figure 1.1 A simple neural network 3 Figure 1.2 Multilayer perceptron neural network 4 Figure 1.3 Convolutional network architecture 5 Figure 1.4 Convolutional layer example 6 Figure 1.5 Example of max pooling layer having 2 × 2 kernel size 7 Figure 1.6 Sigmoid (left), Tanh (right) 8 Figure 1.7 ReLU (left), Leaky ReLU (right) 9 Figure 1.8 The GANs architecture 13 Figure 1.9 The Generator network 14 Figure 1.10 The Discriminator network 15 Figure 4.1 Different zones and headline of Gurmukhi script 25 Figure 4.2 Consonants used in Gurmukhi script 26 Figure 4.3 Consonants,
Load more

Recommended publications
  • Schwa Deletion: Investigating Improved Approach for Text-To-IPA System for Shiri Guru Granth Sahib
    ISSN (Online) 2278-1021 ISSN (Print) 2319-5940 International Journal of Advanced Research in Computer and Communication Engineering Vol. 4, Issue 4, April 2015 Schwa Deletion: Investigating Improved Approach for Text-to-IPA System for Shiri Guru Granth Sahib Sandeep Kaur1, Dr. Amitoj Singh2 Pursuing M.E, CSE, Chitkara University, India 1 Associate Director, CSE, Chitkara University , India 2 Abstract: Punjabi (Omniglot) is an interesting language for more than one reasons. This is the only living Indo- Europen language which is a fully tonal language. Punjabi language is an abugida writing system, with each consonant having an inherent vowel, SCHWA sound. This sound is modifiable using vowel symbols attached to consonant bearing the vowel. Shri Guru Granth Sahib is a voluminous text of 1430 pages with 511,874 words, 1,720,345 characters, and 28,534 lines and contains hymns of 36 composers written in twenty-two languages in Gurmukhi script (Lal). In addition to text being in form of hymns and coming from so many composers belonging to different languages, what makes the language of Shri Guru Granth Sahib even more different from contemporary Punjabi. The task of developing an accurate Letter-to-Sound system is made difficult due to two further reasons: 1. Punjabi being the only tonal language 2. Historical and Cultural circumstance/period of writings in terms of historical and religious nature of text and use of words from multiple languages and non-native phonemes. The handling of schwa deletion is of great concern for development of accurate/ near perfect system, the presented work intend to report the state-of-the-art in terms of schwa deletion for Indian languages, in general and for Gurmukhi Punjabi, in particular.
    [Show full text]
  • The Original Pronunciation of Sanskrit Devanàgará – Transliteration – IPA-Symbols
    The Original Pronunciation of Sanskrit DevanÀgarÁ – Transliteration – IPA-Symbols $ a n$D À DØ i L Á LØ u X A Â XØ ? Ã `C C Å `CØ CØ Æ O C # e HØ #H ai DeØ, $DH o RØ $D( au DØe8 N{ k N R kh N+ J g J gh J+ Ç 1 F c WeÝ ' ch WeÝ+ M j GeÛ + jh GeÛ+ _ È × T Ê Þ 4 Êh Þ+ I Ë É ) Ëh É+ > É Ö W t W Z th W+ G{ d G [ dh G+ Q n Q S p S { ph S+ E b E bh E+ P m P \ y M U{ r `O l O Y v Y9 ] Ì Ý Í V s V K h Ù Drafted by Maciej Zieba and Ulrich Stiehl under the auspices of Manfred Mayrhofer. ! Ï [ Improvements by Jost Gippert, Madhav Deshpande, Sunder Hattangadi, John Smith and others. This chart is a compromise, since the original pronunciation of Sanskrit Î YDULRXV is not exactly known in every detail. – 06/09/2002/us. Notes: 1. $ seems to have been pronounced originally as [n] or as [], possibly never as [D]. Not even the pronunciation of this most often used letter $ is exactly known! 2. The original pronunciation of is not known. It occurs only in the verb dS(kÆp). 3. U{seems to have been pronounced as [`] or as [], and likewise the liquid seems to have been pronounced as syllabic [`C] (notation: [`]+ [ C]) or as syllabic [C]. 4. The pronunciation of the semi-vowel Y seems to have been either [Y] or [9].
    [Show full text]
  • The Number-System of Algebra : Treated Theoretically and Historically
    - ; THE NUMBER-SYSTEM OF ALGEBRA TKEATED THEORETICALLY AND HISTORICALLY BY HENRY B. FINE, PH.D. PROFESSOR OF MATHEMATICS IN PRINCETON UNIVERSITY SECOND EDITION, WITH CORRECTIONS BOSTON, U.S.A. D. C. HEATH & CO., PUBLISHERS 1907 COPYRIGHT, 1890, BY HENRY B. FINE. 66 f 6 T PREFACE. THE theoretical part of this little book is an elementary of exposition the nature of the number concept, of the posi- tive integer, and of the four artificial forms of number which, with the positive integer, constitute the "number- " system of algebra, viz. the negative, the fraction, the irra- tional, and the imaginary. The discussion of the artificial numbers follows, in general, the same lines as my pam- phlet : On the Forms of Number arising in Common Algebra, but it is much more exhaustive and thorough- going. The point of view is the one first suggested by Peacock and Gregory, and accepted by mathematicians gen- erally since the discovery of quaternions and the Ausdeh- nungslehre of Grassmann, that algebra is completely defined formally by the laws of combination to which its funda- mental operations are subject; that, speaking generally, these laws alone define the operations, and the operations the various artificial numbers, as their formal or symbolic results. This doctrine was fully developed for the neg the fraction, and the imaginary by Hankel, in his Complexe Zahlensystemen, in 1867, and made complete by Cantor's beautiful theory of the irrational in 1871, but it has not as yet received adequate treatment in English. this kind is Any large degree of originality in work of from a naturally out of the question.
    [Show full text]
  • Shahmukhi to Gurmukhi Transliteration System: a Corpus Based Approach
    Shahmukhi to Gurmukhi Transliteration System: A Corpus based Approach Tejinder Singh Saini1 and Gurpreet Singh Lehal2 1 Advanced Centre for Technical Development of Punjabi Language, Literature & Culture, Punjabi University, Patiala 147 002, Punjab, India [email protected] http://www.advancedcentrepunjabi.org 2 Department of Computer Science, Punjabi University, Patiala 147 002, Punjab, India [email protected] Abstract. This research paper describes a corpus based transliteration system for Punjabi language. The existence of two scripts for Punjabi language has created a script barrier between the Punjabi literature written in India and in Pakistan. This research project has developed a new system for the first time of its kind for Shahmukhi script of Punjabi language. The proposed system for Shahmukhi to Gurmukhi transliteration has been implemented with various research techniques based on language corpus. The corpus analysis program has been run on both Shahmukhi and Gurmukhi corpora for generating statistical data for different types like character, word and n-gram frequencies. This statistical analysis is used in different phases of transliteration. Potentially, all members of the substantial Punjabi community will benefit vastly from this transliteration system. 1 Introduction One of the great challenges before Information Technology is to overcome language barriers dividing the mankind so that everyone can communicate with everyone else on the planet in real time. South Asia is one of those unique parts of the world where a single language is written in different scripts. This is the case, for example, with Punjabi language spoken by tens of millions of people but written in Indian East Punjab (20 million) in Gurmukhi script (a left to right script based on Devanagari) and in Pakistani West Punjab (80 million), written in Shahmukhi script (a right to left script based on Arabic), and by a growing number of Punjabis (2 million) in the EU and the US in the Roman script.
    [Show full text]
  • Sanskrit Alphabet
    Sounds Sanskrit Alphabet with sounds with other letters: eg's: Vowels: a* aa kaa short and long ◌ к I ii ◌ ◌ к kii u uu ◌ ◌ к kuu r also shows as a small backwards hook ri* rri* on top when it preceeds a letter (rpa) and a ◌ ◌ down/left bar when comes after (kra) lri lree ◌ ◌ к klri e ai ◌ ◌ к ke o au* ◌ ◌ к kau am: ah ◌ं ◌ः कः kah Consonants: к ka х kha ga gha na Ê ca cha ja jha* na ta tha Ú da dha na* ta tha Ú da dha na pa pha º ba bha ma Semivowels: ya ra la* va Sibilants: sa ш sa sa ha ksa** (**Compound Consonant. See next page) *Modern/ Hindi Versions a Other ऋ r ॠ rr La, Laa (retro) औ au aum (stylized) ◌ silences the vowel, eg: к kam झ jha Numero: ण na (retro) १ ५ ॰ la 1 2 3 4 5 6 7 8 9 0 @ Davidya.ca Page 1 Sounds Numero: 0 1 2 3 4 5 6 7 8 910 १॰ ॰ १ २ ३ ४ ६ ७ varient: ५ ८ (shoonya eka- dva- tri- catúr- pancha- sás- saptán- astá- návan- dásan- = empty) works like our Arabic numbers @ Davidya.ca Compound Consanants: When 2 or more consonants are together, they blend into a compound letter. The 12 most common: jna/ tra ttagya dya ddhya ksa kta kra hma hna hva examples: for a whole chart, see: http://www.omniglot.com/writing/devanagari_conjuncts.php that page includes a download link but note the site uses the modern form Page 2 Alphabet Devanagari Alphabet : к х Ê Ú Ú º ш @ Davidya.ca Page 3 Pronounce Vowels T pronounce Consonants pronounce Semivowels pronounce 1 a g Another 17 к ka v Kit 42 ya p Yoga 2 aa g fAther 18 х kha v blocKHead
    [Show full text]
  • Contribution to the UN Secretary-General's 2018 Report
    COMMISSION ON SCIENCE AND TECHNOLOGY FOR DEVELOPMENT (CSTD) Twenty-second session Geneva, 13 to 17 May 2019 Submissions from entities in the United Nations system and elsewhere on their efforts in 2018 to implement the outcome of the WSIS Submission by Internet Corporation for Assigned Names and Numbers This submission was prepared as an input to the report of the UN Secretary-General on "Progress made in the implementation of and follow-up to the outcomes of the World Summit on the Information Society at the regional and international levels" (to the 22nd session of the CSTD), in response to the request by the Economic and Social Council, in its resolution 2006/46, to the UN Secretary-General to inform the Commission on Science and Technology for Development on the implementation of the outcomes of the WSIS as part of his annual reporting to the Commission. DISCLAIMER: The views presented here are the contributors' and do not necessarily reflect the views and position of the United Nations or the United Nations Conference on Trade and Development. 2018 ANNUAL REPORT TO UNCTAD: ICANN CONTRIBUTION Progress made in the implementation of and follow-up to the outcomes of the World Summit on the Information Society at the regional and international levels Executive Summary ICANN is pleased and honoured be invited to contribute to this annual UNCTAD Report. We value our involvement with, and contribution to, the overall WSIS process and to our relationship with the UN Commission on Science and Technology for Development (CSTD). 2018 has been a busy and important year for ICANN and for the Internet Governance Ecosystem in general; with the ITU Plenipotentiary taking place in Dubai and the IGF in Paris.
    [Show full text]
  • Pronunciation
    PRONUNCIATION Guide to the Romanized version of quotations from the Guru Granth Saheb. A. Consonants Gurmukhi letter Roman Word in Roman Word in Gurmukhi Meaning Letter letters using the letters using the relevant letter relevant letter from from the second the first column column S s Sabh sB All H h Het ihq Affection K k Krodh kroD Anger K kh Khayl Kyl Play G g Guru gurU Teacher G gh Ghar Gr House | ng Ngyani / gyani i|AwnI / igAwnI Possessing divine knowledge C c Cor cor Thief C ch Chaata Cwqw Umbrella j j Jahaaj jhwj Ship J jh Jhaaroo JwVU Broom \ ny Sunyi su\I Quiet t t Tap t`p Jump T th Thag Tg Robber f d Dar fr Fear F dh Dholak Folk Drum x n Hun hux Now q t Tan qn Body Q th Thuk Quk Sputum d d Den idn Day D dh Dhan Dn Wealth n n Net inq Everyday p p Peta ipqw Father P f Fal Pl Fruit b b Ben ibn Without B bh Bhagat Bgq Saint m m Man mn Mind X y Yam Xm Messenger of death r r Roti rotI Bread l l Loha lohw Iron v v Vasai vsY Dwell V r Koora kUVw Rubbish (n) in brackets, and (g) in brackets after the consonant 'n' both indicate a nasalised sound - Eg. 'Tu(n)' meaning 'you'; 'saibhan(g)' meaning 'by himself'. All consonants in Punjabi / Gurmukhi are sounded - Eg. 'pai-r' meaning 'foot' where the final 'r' is sounded. 3 Copyright Material: Gurmukh Singh of Raub, Pahang, Malaysia B.
    [Show full text]
  • Punjabi Machine Transliteration Muhammad Ghulam Abbas Malik
    Punjabi Machine Transliteration Muhammad Ghulam Abbas Malik To cite this version: Muhammad Ghulam Abbas Malik. Punjabi Machine Transliteration. 21st international Conference on Computational Linguistics (COLING) and the 44th Annual Meeting of the ACL, Jul 2006, Sydney, France. pp.1137-1144. hal-01002160 HAL Id: hal-01002160 https://hal.archives-ouvertes.fr/hal-01002160 Submitted on 15 Jan 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Punjabi Machine Transliteration M. G. Abbas Malik Department of Linguistics Denis Diderot, University of Paris 7 Paris, France [email protected] Transliteration refers to phonetic translation Abstract across two languages with different writing sys- tems (Knight & Graehl, 1998), such as Arabic to Machine Transliteration is to transcribe a English (Nasreen & Leah, 2003). Most prior word written in a script with approximate work has been done for Machine Translation phonetic equivalence in another lan- (MT) (Knight & Leah, 97; Paola & Sanjeev, guage. It is useful for machine transla- 2003; Knight & Stall, 1998) from English to tion, cross-lingual information retrieval, other major languages of the world like Arabic, multilingual text and speech processing. Chinese, etc. for cross-lingual information re- Punjabi Machine Transliteration (PMT) trieval (Pirkola et al, 2003), for the development is a special case of machine translitera- of multilingual resources (Yan et al, 2003; Kang tion and is a process of converting a word & Kim, 2000) and for the development of cross- from Shahmukhi (based on Arabic script) lingual applications.
    [Show full text]
  • Inventory of Romanization Tools
    Inventory of Romanization Tools Standards Intellectual Management Office Library and Archives Canad Ottawa 2006 Inventory of Romanization Tools page 1 Language Script Romanization system for an English Romanization system for a French Alternate Romanization system catalogue catalogue Amharic Ethiopic ALA-LC 1997 BGN/PCGN 1967 UNGEGN 1967 (I/17). http://www.eki.ee/wgrs/rom1_am.pdf Arabic Arabic ALA-LC 1997 ISO 233:1984.Transliteration of Arabic BGN/PCGN 1956 characters into Latin characters NLC COPIES: BS 4280:1968. Transliteration of Arabic characters NL Stacks - TA368 I58 fol. no. 00233 1984 E DMG 1936 NL Stacks - TA368 I58 fol. no. DIN-31635, 1982 00233 1984 E - Copy 2 I.G.N. System 1973 (also called Variant B of the Amended Beirut System) ISO 233-2:1993. Transliteration of Arabic characters into Latin characters -- Part 2: Lebanon national system 1963 Arabic language -- Simplified transliteration Morocco national system 1932 Royal Jordanian Geographic Centre (RJGC) System Survey of Egypt System (SES) UNGEGN 1972 (II/8). http://www.eki.ee/wgrs/rom1_ar.pdf Update, April 2004: http://www.eki.ee/wgrs/ung22str.pdf Armenian Armenian ALA-LC 1997 ISO 9985:1996. Transliteration of BGN/PCGN 1981 Armenian characters into Latin characters Hübschmann-Meillet. Assamese Bengali ALA-LC 1997 ISO 15919:2001. Transliteration of Hunterian System Devanagari and related Indic scripts into Latin characters UNGEGN 1977 (III/12). http://www.eki.ee/wgrs/rom1_as.pdf 14/08/2006 Inventory of Romanization Tools page 2 Language Script Romanization system for an English Romanization system for a French Alternate Romanization system catalogue catalogue Azerbaijani Arabic, Cyrillic ALA-LC 1997 ISO 233:1984.Transliteration of Arabic characters into Latin characters.
    [Show full text]
  • A Message from Afar: Fact Sheet 3 (PDF)
    3 What’s the Message? Here’s your signal The detection of a signal from another world would be a most remarkable moment in human history. However, if we detect such a signal, is it just a beacon from their technology, without any content, or does it contain information or even a message? Does it resemble sound, or is it like interstellar e-mail? Can we ever understand such a message? This appears to be a tremendous challenge, given that we still have many scripts from our own antiquity that remain undeciphered, despite many serious attempts, over hundreds of years. – And we know far more about humanity than about extra-terrestrial intelligence… We are facing all the complexities involved in understanding and glimpsing the intellect of the author, while the world’s expectations demand immediacy of information. So, where do we begin? Structure and language Information stands out from randomness, it is based on structures. The problem goal we face, after we detect a signal, is to first separate out those information-carrying signals from other phenomena, without being able to engage in a dialogue, and then to learn something about the structure of their content in the passing. This means that we need a suitable filter. We need a way of separating out the interesting stuff; we need a language detector. While identifying the location of origin of a candidate signal can rule out human making, its content could involve a vast array of possible structures, some of which may be beyond our knowledge or imagination; however, for identifying intelligence that shares any pattern with our way of processing and transmitting information, the collective knowledge and examples here on Earth are a good starting point.
    [Show full text]
  • A Review on Handwritten Devnagari Numerals Recognition Using Support Vector Machine
    Proceedings of VESCOMM-2016 4th NATIONAL CONFERENCE ON “RECENT TRENDES IN VLSI, EMBEDED SYSTEM, SIGNAL PROCESSING AND COMMUNICATION In Association with “The Institution of Engineers (India)” and IJRPET February 12th, 2016 Paper ID: VESCOMM03 A REVIEW ON HANDWRITTEN DEVNAGARI NUMERALS RECOGNITION USING SUPPORT VECTOR MACHINE Rupali Vitthalrao Suryawanshi Department of Electronics Engineering, Bharatratna Indira Gandhi College, Solapur, India, 413006 [email protected] Abstract— Handwriting has continued to persist as a mean of SVM stands for Support Vector Machine and this method of communication and recording information in day-to-day life even recognition is gaining immense popularity now-a-days. SVM with the invention of new technologies. Natural handwriting is classifier gives better results as compared to the other one of the easiest ways of information exchange between a human classifiers for the handwritten numeral recognition of Kannada and a computer. Handwriting recognition has attracted many script in [3]. In [6], SVM approach is used to recognize researchers across the world since many years. Recognition of strokes in Telugu script. The set of strokes are segmented into online handwritten Devanagari numerals is a goal of many subsets based on the relative position of the stroke in a research efforts in the pattern recognition field The main goal of character. An SVM based classifier is built for recognition of the work is the recognition of online hand written Devanagari strokes in each subset. A rule based approach is used to numerals using support vector machine. In the data collection recognize a character from the sequence of stroke classes phase, co-ordinate points of the input handwritten numeral are given by the stroke classifier.
    [Show full text]
  • Elements of South-Indian Palaeography, from the Fourth To
    This is a reproduction of a library book that was digitized by Google as part of an ongoing effort to preserve the information in books and make it universally accessible. https://books.google.com ELEMENTS SOUTH-INDIAN PALfi3&BAPBY FROM THE FOURTH TO THE SEVENTEENTH CENTURY A. D. BEIN1 AN INTRODUCTION TO ?TIK STUDY OF SOUTH-INDIAN INSCRIPTIONS AND MSS. BY A. C. BURNELL HON'. PH. O. OF TUE UNIVERSITY M. K. A, ri'VORE PIS I. A SOClfcTE MANGALORE \ BASEL MISSION BOOK & TRACT DEPOSITORY ft !<3 1874 19 Vi? TRUBNER & Co. 57 & 69 LUDOATE HILL' . ' \jj *£=ggs3|fg r DISTRIBUTION of S INDIAN alphabets up to 1550 a d. ELEMENTS OF SOUTH-INDIAN PALEOGRAPHY FROM THE FOURTH TO THE SEVENTEENTH CENTURY A. D. BEING AN INTRODUCTION TO THE STUDY OF SOUTH-INDIAN INSCRIPTIONS AND MSS. BY A. p. j^URNELL HON. PH. D. OF THE UNIVERSITY OF STRASSBUB.G; M. R. A. S.; MEMBKE DE LA S0CIETE ASIATIQUE, ETC. ETC. MANGALORE PRINTED BY STOLZ & HIRNER, BASEL MISSION PRESS 1874 LONDON TRtlBNER & Co. 57 & 59 LUDGATE HILL 3« w i d m « t als ^'ctdjcn kr §anltekcit fiir Mc i|jm bdic<jcnc JJoctorMvk ttcsc fetlings^kit auf rincm fejjcr mtfrckntcn Jfclk bet 1®4 INTRODUCTION. I trust that this elementary Sketch of South-Indian Palaeography may supply a want long felt by those who are desirous of investigating the real history of the peninsula of India. Trom the beginning of this century (when Buchanan executed the only archaeological survey that has ever been done in even a part of the South of India) up to the present time, a number of well meaning persons have gone about with much simplicity and faith collecting a mass of rubbish which they term traditions and accept as history.
    [Show full text]