Abstract:
Text in images and videos contain useful information for automatic annotation,
indexing, and structuring of images and videos. Extraction of this information
involves detection, localization, tracking, extraction, enhancement, and recognition
of the text from a given image and videos. However, variations of text due to differences
in size, style, orientation, and alignment, as well as low image contrast and complex
background make the problem of automatic text extraction extremely challenging.In the
complete process of text extraction, text detection is the primary and fundamental step.
We can increase the performance of the text detection by giving high-resolution images or
video frames instead of low-resolution images or video frames. Here, Super-resolution can
be used to produce the high-resolution image or video frame. In high-resolution images or
video frames, there is more pixel density and thus provides finer details of the image or
scene. In this report, we talk about how we can increase the range of different size text
detected from videos using super resolution. More detected text from a video will imply
performance increase in text recognition.
