Processing of Historic Inscription Images



The study and analysis of epigraphy is important for knowing about the past. From around third century to modern times, about 90,000 inscriptions have been discovered from different parts of India.



This work is an output of DST-funded Project IDH. This work would not have been completed without the help of Ayush, Aman, Rishi Pandey and Geetanjali Bhola.


  1. 1.
    Salomon R (1998) Indian epigraphy. A guide to the study of inscriptions in Sanskrit, Prakrit, and the other Indo-Aryan languages. Oxford University PressGoogle Scholar
  2. 2.
    Verghese A, Dallapiccola, AL (eds) (2011) South India under Vijayanagara, art and archaeology. Oxford University PressGoogle Scholar
  3. 3.
    Hyvarinen A, Karhunen J, Oja E (2004) Independent component analysis, vol 46. WileyGoogle Scholar
  4. 4.
    Sreedevi I et al (2013) Enhancement of inscription images. In: 2013 National Conference on Communications (NCC). IEEE. “978-1-4673-5952-8/13/$ 31.00 2013 IEEE”Google Scholar
  5. 5.
    Sreedevi I et al (2013) Ngfica based digitization of historic inscription images. ISRN Signal Process 2013:7, Article ID 735857.
  6. 6.
    Jayanthi N et al (2014) Digitization of historic inscription images using cumulants based simultaneous blind source extraction. In: Proceedings of the 2014 Indian conference on computer vision graphics and image processing. ACM. “Copyright 2014 ACM 978-1-4503-3061-9/14/12 ...$15.00
  7. 7.
    Amari S-I, Cichocki A, Yang HH (1996) A new learning algorithm for blind signal separation. Adv Neural Inf Process Syst 757–763Google Scholar
  8. 8.
    Amari S, Douglas S (2001) Why natural gradient? Brain Style Information Systems Group, JapanGoogle Scholar
  9. 9.
    Nery MS et al (2005) Determining the appropriate feature set for fish classification tasks. In: XVIII Brazilian symposium on computer graphics and image processing (SIBGRAPI’05). IEEEGoogle Scholar
  10. 10.
    Optical character recognition.
  11. 11.
    Cichocki A, Amari S-I (2002) Adaptive blind signal and image processing: learning algorithms and applications, vol 1. WileyGoogle Scholar
  12. 12.
    Tonazzini Anna, Bedini Luigi, Salerno Emanuele (2004) Independent component analysis for document restoration. Doc Anal Recogn 7(1):17–27Google Scholar
  13. 13.
    Cruces-Alvarez SA, Cichocki A, Amari S-I (2004) From blind signal extraction to blind instantaneous signal separation: criteria, algorithms, and stability. IEEE Trans Neural Netw 15(4):859–873CrossRefGoogle Scholar
  14. 14.
    Cruces-Alvarez Sergio A, Cichocki Andrzej, Amari Shun-Ichi (2002) On a new blind signal extraction algorithm: different criteria and stability analysis. IEEE Signal Process Lett 9(8):233–236CrossRefGoogle Scholar
  15. 15.
    Katsumata Naoto, Matsuyama Yasuo (2005) Database retrieval for similar images using ICA and PCA bases. Eng Appl Artif Intell 18(6):705–717CrossRefGoogle Scholar
  16. 16.
    Huber PJ (1985) Projection pursuit. In: The annals of statistics, pp 435–475Google Scholar
  17. 17.
    Blaschke Tobias, Wiskott Laurenz (2004) CuBICA: Independent component analysis by simultaneous third-and fourth-order cumulant diagonalization. IEEE Trans Signal Process 52(5):1250–1256MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Otsu Nobuyuki (1975) A threshold selection method from gray-level histograms. Automatica 11(285-296):23–27Google Scholar
  19. 19.
    Garainl, et al (2008) Machine reading of camera-held low quality text images: an ICA-based image enhancement approach for improving OCR accuracy. In: 2008 19th International Conference on Pattern Recognition, ICPR 2008. IEEEGoogle Scholar
  20. 20.
    Pratikakis I, Gatos B, Ntirogiannis K (2010) H-DIBCO 2010-handwritten document image binarization competition. In: 2010 international conference on frontiers in handwriting recognition (ICFHR). IEEEGoogle Scholar
  21. 21.
    Pratikakis I, Gatos B, Ntirogiannis K (2013) ICDAR 2013 document image binarization contest (DIBCO 2013). In: 2013 12th international conference on document analysis and recognition (ICDAR). IEEEGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Delhi Technological UniversityDelhiIndia
  2. 2.CEERI PilaniPilaniIndia

Personalised recommendations