Implementing Video OCR along with SWT Technique for Video indexing and Analysis

Full Text (PDF, 427KB), PP.27-35

Views: 0 Downloads: 0


Paruchuru Grishman 1,* Akula Rajitha 1 Mohammed Khaja Moinuddin 1 Mannava Subhramanaya Sreekar 1 Siddam Jayanth 1

1. IARE/IT/Hyderabad, Telangana, 500043

* Corresponding author.


Received: 4 Jun. 2022 / Revised: 29 Jul. 2022 / Accepted: 25 Aug. 2022 / Published: 8 Feb. 2023

Index Terms

Optical Character Recognition, Tesseract, Binarization, Python, Segmentation, Stroke Width Transform, Open CV, Video Indexing, Image Processing.


The main purpose of this paper is to expand the usage of OCR (Optical character recognition) as this is only implemented over images and to extend this Video OCR is introduced in a way to help to retrieve the information from the video without playing the video. Video OCR is executed with the assistance of OpenCv2 module and PyTesseract [7] at the side of SWT approach which all pretty collectively make an ideal aggregate to offer an appropriate content from the video (i.e., Lecture video or any kind of video which has slides or text on the background of the video) [2,4].This technique is performed in a well-designed along with easy steps to provide us an correct end result of the facts from the video into textual files. In addition to this we also added Speech Recognition module within the project to support the video along with the text file. This speech delivered by the faculty (i.e., instructor/educator/teacher), or an educator will be also resulted in a text file.

Cite This Paper

Paruchuru Grishman, Akula Rajitha, Mohammed Khaja Moinuddin, Mannava Subhramanaya Sreekar, Siddam Jayanth, "Implementing Video OCR along with SWT Technique for Video indexing and Analysis", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.13, No.1, pp. 27-35, 2023. DOI:10.5815/ijwmt.2023.01.03


[1]Karez Abdulwahhab Hamad,Mehmet Kaya :A Detailed Analysis of Optical Character Recognition Technology.

[2]Jay Dilipbhai Thanki, Priyank Dineshbhai Davda, Dr. Priya Swaminarayan :A Review on OCR Technology

[3]Jamshed Memon, Maira Sami, Rizwan Ahmed Khan,Mueen Uddin: Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)

[4]Boris Epshtein, Eyal Ofek,Yonatan Wexler :Detecting Text in Natural Scenes with Stroke Width Transform.

[5]Mahitha G, Surabhi K, Rahul Kumar: Enhanced Stroke Width Transform to Detect Text Regions in Natural Scene Images.

[6]Chirag Patel, Atul Patel, Dharmendra Patel :Optical Character Recognition by Open-source OCR Tool Tesseract.

[7]Muskan Chawala , Rachna Jain, Preeti  Nagrath :Implementation of Tesseract Algorithm to Extract Text from Different Images.

[8]Minghui Liao, Zhaoyi Wan , Cong Yao, Kai Chen, Xiang Bai-Real-time Scene Text Detection with Differentiable Binarization

[9]Karishma Tyagi, Vedant Rastogi  Survey on Character Recognition using OCR Techniques  

[10]Shiravale, Sankirti & Kamade, P. (2011). Video OCR for Video Indexing. International Journal of Engineering and Technology. 3. 10.7763/IJET.2011.V3.239.

[11]Avinash Verma, Deepak Kumar Singh,"Text Deblurring Using OCR Word Confidence", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.9, No.1, pp.33-40, 2017.DOI: 10.5815/ijigsp.2017.01.05

[12]C. Gonzalez Richard E. Woods “Digital Image Processing” Book Third Edition Rafael Interactive Pearson International Edition prepared by Pearson Education PEARSON Prentice Hall.

[13]Shamik Tiwari, V. P. Shukla, and A. K. Singh “Review of Motion Blur Estimation Techniques” Journal of Image and Graphics Vol. 1, No. 4, December 2013.

[14]Kishore R. Bhagat,Puran Gour "Novel Approach to Estimate Motion Blur Kernel Parameters and Comparative Study of Restoration Techniques"International Journal of Computer Applications (0975 – 8887) Volume 72– No.17, June 2013.

[15]Nam-Yong Lee “Block-iterative Richardson-Lucy methods for image deblurring" Lee EURASIP Journal on Image and Video Processing (2015) Springer 2015:14 DOI 10.1186/s13