Journal of Critical Reviews ISSN- 2394-5125 Vol 7, Issue 6, 2020 Review Article FUZZY BASE ARTIFICIAL NEURAL NETWORK MODEL FOR TEXT EXTRACTION FROM IMAGES V. Lakshman Narayana1, B. Naga Sudheer2, Venkata Rao Maddumala3,P.Anusha4 1Department of Information Technology, Vignan’s Nirula Institute of Technology & Science for Women, Peda Palakaluru, Guntur, Andhra Pradesh, India.
[email protected] 2Asst.Professor, Department of IT, Vignan's Foundation for Science, Technology & Research (Deemed to be University), Vadlamudi, Guntur, Andhra Pradesh, India.
[email protected] 3Department of Information Technology, Vignan’s Nirula Institute of Technology & Science for Women, Peda Palakaluru, Guntur, Andhra Pradesh, India. 4Department of Information Technology, Vignan’s Nirula Institute of Technology & Science for Women, Peda Palakaluru, Guntur, Andhra Pradesh, India. Received: 15.02.2020 Revised: 19.03.2020 Accepted: 05.04.2020 Abstract Content Extraction assumes a significant job in discovering essential and important data. Content extraction includes discovery, restriction, following, binarization, extraction, improvement and acknowledgment of the content from the given picture. This paper proposes a bi-leveled picture characterization framework to group printed and transcribed reports into totally unrelated predefined classes. In the present article, we propose a Fuzzy guideline guided novel strategy that is utilitarian without any outer intercession during execution. The Fuzzy validation processor utilizes subtleties of divider speed and force, just as change, to decide if the deliberate reverberation signal part to be separated genuinely speaks to the divider speed as it were. Test results propose that this methodology is a proficient one in contrast with various different strategies widely tended to in writing.