For content based indexing of videos, numerous tools and techniques are pipe-lined. The major challenge that these techniques face is the accuracy of index points generated. This paper presents an efficient way to extract text from video frames along with its timestamps. Text extraction takes place in a three-step method which combines pre-processing of extracted Video Frames, similarity measurement for removing ambiguous frames and finally text extraction using PyTesseract Optical Character Recognition. The educational videos with presentations are prioritised. Text extraction is applied upon the headings of that presentation. These extracted keywords are referred to as Index Points through out the article.

对于基于内容的视频索引，许多工具和技术都是流水线式的。这些技术面临的主要挑战是生成的索引点的准确性。本文提出了一种从视频帧中提取文本及其时间戳的有效方法。文本提取采用三步方法进行，该方法结合了提取的视频帧的预处理、用于去除歧义帧的相似性测量以及最后使用 PyTesseract 光学字符识别的文本提取。带有演示文稿的教育视频优先。文本提取应用于该演示文稿的标题。这些提取的关键字在整篇文章中被称为索引点。