Journal of Innovative Image Processing
IRO Journals
Volume 1 — Issue 1 — September 2019

A SMART IMAGE PROCESSING ALGORITHM FOR TEXT RECOGNITION, INFORMATION EXTRACTION AND VOCALIZATION FOR THE VISUALLY CHALLENGED

https://doi.org/10.36548/jiip.2019.1.004
Samuel Manoharan
Professor, Department of Electronics, Bharathiyar College of Engineering and Technology
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How to Cite

Manoharan, Samuel. 2019. “A SMART IMAGE PROCESSING ALGORITHM FOR TEXT RECOGNITION, INFORMATION EXTRACTION AND VOCALIZATION FOR THE VISUALLY CHALLENGED”. Journal of Innovative Image Processing 1 (1): 31-38. https://doi.org/10.36548/jiip.2019.1.004.
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Keywords

— Image Processing
— LattePanda Alpha
— text to speech
— vocalization
— OCR
Published: 30-09-2019

Abstract

This paper proposes a smart algorithm for image processing by means of recognition of text, extraction of information and vocalization for the visually challenged. The system uses LattePanda Alpha system on board that processes the scanned images. The image is categorized into its equivalent alphanumeric characters following pre-processing, segmentation, extraction of features and post-processing of the scanned or image based information. Further, a text to speech synthesizer is used for vocalization processed content. In converting handwritten scripts, the system offers an accuracy of 97% in conversion. This also depends on the legibility of the data. The time delay for the entire conversion process is also analysed and the efficiency of the system is estimated.

References

  1. Joshi, AV Kumar, T. Prabhu Madhan, and S. Raj Mohan. "Automated electronic pen aiding visually impaired in reading, visualizing and understanding textual contents." In 2011 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY, pp. 1-6. IEEE, 2011.
  2. Shanmugam, K., and B. Vanathi. "Hardcopy Text Recognition and Vocalization for Visually Impaired and Illiterates in Bilingual Language." In Computational Intelligence and Sustainable Systems, pp. 151-163. Springer, Cham, 2019.
  3. Karthikeyan, A., U. Kripanya, M. Manish, S. Nivetha, H. Prabanjan, and K. Ramkumar. "Cartable Camera Based Assistive Text Recognition for Visually Impaired."
  4. Monticelli, Cíntia, Regina De Oliveira Heidrich, Ronaldo Rodrigues, Ewerton Cappelatti, Rodrigo Goulart, Ricardo Oliveira, and Eduardo Velho. "Text Vocalizing Desktop Scanner for Visually Impaired People." In International Conference on Human-Computer Interaction, pp. 62-67. Springer, Cham, 2018.
  5. Dhulekar, Pravin A., Niharika Prajapatr, Tejal A. Tribhuvan, and Karishma S. Godse. "Automatic voice generation system after street board identification for visually impaired." In 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), pp. 91-96. IEEE, 2016.
  6. Zandifar, Ali, and Antoine Chahine. "A video based interface to textual information for the visually impaired." In Proceedings of the 4th IEEE international Conference on Multimodal interfaces, p. 325. IEEE Computer Society, 2002.
  7. Rajesh, M., Bindhu K. Rajan, Ajay Roy, K. Almaria Thomas, Ancy Thomas, T. Bincy Tharakan, and C. Dinesh. "Text recognition and face detection aid for visually impaired person using Raspberry PI." In 2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT), pp. 1-5. IEEE, 2017.
  8. Verma, Prabhat, Raghuraj Singh, and Avinash Kumar Singh. "A framework for the next generation screen readers for visually impaired." International Journal of Computer Applications (2012).
  9. Patil, Mrunmayee, and Ramesh Kagalkar. "An Automatic Approach for Translating Simple Images into Text Descriptions and Speech for Visually Impaired People." International Journal of Computer Applications 975 (2015): 8887.
  10. Arun, M., S. S. Salvadiswar, and J. Sibidharan. "Design and Implementation of Text To Speech Conversion for Visually Impaired Using ‘i’Novel Algorithm." Journal on Today's Ideas-Tomorrow's Technologies 2, no. 1 (2014).
  11. Ragavi, K., Priyanka Radja, and S. Chithra. "Portable text to speech converter for the visually impaired." In Proceedings of the International Conference on Soft Computing Systems, pp. 751-758. Springer, New Delhi, 2016.
  12. Chollet, Gérard, Kevin McTait, and Dijana Petrovska-Delacrétaz. "Data driven approaches to speech and language processing." In International School on Neural Networks, Initiated by IIASS and EMFCSC, pp. 164-198. Springer, Berlin, Heidelberg, 2004.
  13. Kalaivani, K., R. Praveena, V. Anjalipriya, and R. Srimeena. "Real time implementation of image recognition and text to speech conversion." Int. J. Adv. Res. Technol 2 (2014): 171-175.
  14. Kuruvilla, Jiss, Dhanya Sukumaran, Anjali Sankar, and Siji P. Joy. "A review on image processing and image segmentation." In 2016 international conference on data mining and advanced computing (SAPIENCE), pp. 198-203. IEEE, 2016.
  15. Victor, Domínguez M., Fidalgo F. Eduardo, Rubel Biswas, Enrique Alegre, and Laura Fernández-Robles. "Application of Extractive Text Summarization Algorithms to Speech-to-Text Media." In International Conference on Hybrid Artificial Intelligence Systems, pp. 540-550. Springer, Cham, 2019.
  16. Joshi, Neha. "Text Image Extraction and Summarization." Asian Journal For Convergence In Technology (AJCT) (2019).
  17. Chu, Yung-Long, Hung-En Hsieh, Wen-Hsiung Lin, Hui-Ju Chen, and Chien-Hsing Chou. "Chinese FingerReader: a wearable device to explore Chinese printed text." In ACM SIGGRAPH 2017 Posters, p. 54. ACM, 2017.
  18. Singh, Raghuraj, C. S. Yadav, Prabhat Verma, and Vibhash Yadav. "Optical character recognition (OCR) for printed devnagari script using artificial neural network." International Journal of Computer Science & Communication 1, no. 1 (2010): 91-95.
  19. Kissos, Ido, and Nachum Dershowitz. "OCR error correction using character correction and feature-based word classification." In 2016 12th IAPR Workshop on Document Analysis Systems (DAS), pp. 198-203. IEEE, 2016.
  20. Luther, Willis J., Loren A. Wood, Thomas S. Tullis, and James A. Fontana. "Method and apparatus for extracting text from a structured data file and converting the extracted text to speech." U.S. Patent 5,715,370, issued February 3, 1998.
  21. Deligne, Sabine, Francois Yvon, and Frédéric Bimbot. "Variable-length sequence matching for phonetic transcription using joint multigrams." In Fourth European Conference on Speech Communication and Technology. 1995.
  22. Whibley, Simon, Michael Day, Peter May, and Maureen Pennock. WAV Format Preservation Assessment. Technical Report. British Library. http://wiki. dpconline. org/images/4/46/WAV Assessment v1. 0. pdf, 2016.