Now a days digital video is very popular as an exchange medium
due to large improvement in video recording and compression techniques and
increasing of network-speed. Therefore audiovisual recordings are used more frequently
in e-learning and e-lecturing systems. OCR from videography is a technique that
can locate any text inside a digital video file via reading and  automatic extraction of any notes and captions
that gives the actual information (like – the names of people, places or
description of objects etc.) about the video being presented. Detecting the video-content
requires many technologies like scanning, pre-processing, search strategies, video
segmentation, feature-extraction, recognition etc. Reading the extracted notes
and captions gives more appropriate information to understand the video-content.
Applying OCR on video and combining the results with various detecting techniques
can improve the detection result. Although integrated character recognition in
text-based videos is needed greatly.

                There
are various research fields which concern
character recognition from videos. In character extraction from the video difficulties
are present due to different conditions of title, character size and complex
backgrounds. In video caption resolution of character is lower and the
background complexity is more severe than in other research. The first problem
is low resolution of the characters. An image size is limited
by title, number of scan lines defined in the NTSC standard. Therefore, the resolution
of characters in the video-caption is insufficient to implement stable and
robust OCR-Videography systems. Another problem is the presence of complex backgrounds.
Characters superimposed on videos often have similar hue and brightness to the
background. Presence of these problems in OCR-Videography systems has opened a
new area for research work. OCR from videography is a technique that can
greatly help to locate the topics of interest in a large digital video via the
automatic extraction and reading of captions and notes.

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