The Experimental Implementation of GrabCut for Hardcode Subtitle Extraction

Abstract

In this paper, we describe a relatively convenient way to extract and recognize text from a background in various circumstances of complicity. One general purpose in many applications is to extract hardcode subtitles from videos. Popular hardcode subtitle-rip tools (applications) nowadays follow a similar procedure from text location settings, customized image post-editing to OCR process. The quality of results usually may not be satisfied, and the supporting video formats are limited. Thanks to "GrabCut" image segmentation algorithm and "Tesseract-OCR" technology, we have developed a more augmented version in python for hardcode subtitle extraction on a fixed location, based on many attempts of experimental practice and research. The method we proposed outperforms most of the competitive tools on the quality of results.