Image2Speech– Text Recognition In Images And Converting Recognized Text To Speech

Authors

  • Mohd. Vakil
  • Abhishak Shukla

Keywords:

Digital image processing, optical character recognition, speech modulation, MSER Regions, stroke width algorithm, and image character recognition

Abstract

Around 285 million people worldwide are visually impaired, including close to 39 million blind people.Thishasasignificantimpactonthelivesofpersons who are blind or visually impaired. Even though numerous attempts have been made to assist those who are blind in seeing objects through alternate senses like touch and sound, text-reading technology is still in its infancy. The system in use right now is either constrained in its application or expensive to maintain. Therefore, we require a system that can automatically recognize and read aloud text to a user base of visually impaired people that is both affordableandtrulyefficient.Themaingoalofthisresearch is to develop a program that can identify text characters from turn any natural image into a voice signal. The programme need to carry out the identical action for any uploaded image and PDF file. The application should also havetoolsforpacemodulation, voicechoosingoptions,and storage capability for image to text output. The target audience for this programme can be expanded to include people with special needs who also have learning impairments, young children, and several other societal groups. The text is extracted fromthe image using optical character recognition (OCR), and the Windows
API is utilised to turn the text into speech. The programming language for digital image processing is MATLAB.

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Published

2020-12-21

How to Cite

Mohd. Vakil, & Abhishak Shukla. (2020). Image2Speech– Text Recognition In Images And Converting Recognized Text To Speech. Elementary Education Online, 19(4), 8477–8485. Retrieved from https://ilkogretim-online.org/index.php/pub/article/view/7526

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Section

Articles