Extraction of Character from Visuals and Images Using OpenCV

Author:

Fathima Chandhini S 1,Rashad H 2,Gowseelan K 2,Jayasarathy S 2

Affiliation:

1. Assistant Professor, Department of Information Technology, M.A.M. College of Engineering and Technology,Tiruchirappalli, Tamil Nadu, India

2. UG Student, Department of Information Technology, M.A.M. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India

Abstract

To develop a computer vision system that can accurately extract characters from document pages and image data using the OpenCV library. The system is designed to process a wide range of visual inputs and extract characters with high precision and efficiency. The techniques used to implement the character extraction system, including pre-processing, feature extraction, and classification. The performance of the system is evaluated using a dataset of visual image data from a different type of visual inputs and the output of the system can be accurately extracting characters. In Future, Automated conversion of an image input into a machine-readable file.

Publisher

Technoscience Academy

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference13 articles.

1. Ayush Purohit, Shardul Singh Chauhan, (2016) "Handwritten Character Recognition using Neural Network" International Journal of Computer Science and Information Technologies, Vol. 7.

2. Liana M. Lorigo and Venu Govindaraju, (2006) "Offline Arabic Handwriting Recognition: A Survey", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 28 Issue 5.

3. Mahmood K Jasim, Anwar M Al-Saleh, Alaa Aljanaby, (2013) "A Fuzzy Logic based Handwritten Numeral Recognition System" International Journal of Computer Applications (0975 – 8887) Volume 83 – No 10.

4. Megha Agarwal, Shalika, Vinam Tomar, Priyanka Gupta (2019) "Handwritten Character Recognition using Neural Network and Tensor Flow" International Journal of Innovative Technology and Exploring Engineering ISSN: 2278-3075, Volume-8, Issue- 6S4, April 2019.

5. Mohammed Z. Khedher, Gheith A. Abandah, and Ahmed M. AlKhawaldeh, (2005) "Optimizing Feature Selection for Recognizing Handwritten Arabic Characters", proceedings of World Academy of Science Engineering and Technology, Vol. 4, ISSN 1307-6884.

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