Video OCR for Video Indexing

TL;DR

This paper discusses the importance of effective preprocessing and binarization techniques in video OCR to improve text recognition accuracy for video indexing and search applications.

Contribution

It emphasizes the role of preprocessing, especially binarization, in enhancing video OCR performance for indexing purposes.

Findings

Effective binarization reduces OCR error rates.

Preprocessing significantly improves text recognition in degraded video conditions.

Video OCR can enhance video indexing and retrieval capabilities.

Abstract

Video OCR is a technique that can greatly help to locate the topics of interest in video via the automatic extraction and reading of captions and annotations. Text in video can provide key indexing information. Recognizing such text for search application is critical. Major difficult problem for character recognition for videos is degraded and deformated characters, low resolution characters or very complex background. To tackle the problem preprocessing on text image plays vital role. Most of the OCR engines are working on the binary image so to find a better binarization procedure for image to get a desired result is important.Accurate binarization process minimizes the error rate of video OCR.