An integration text extraction approach in video frame

Text in video frames contains high-level semantic information and thus can contribute significantly to video content analysis and retrieval. Therefore, video text recognition is crucial to the research in all video indexing and summarization. In the processing of video text recognition, in the extraction step, background in the text rows is removed so only the text pixels are left for recognition. Although many efforts have been made for video text extraction, there are still many research works to do. Text extraction from images remains a challenging problem for character recognition applications, due to complex background, unknown text color, degraded text quality caused by the lossy compression, and different language characteristics. In this paper, we present an efficient approach of text extraction based on multiple frame integration and stroke filter. Firstly text block filtering and integration are used to obtain the clean background and clear text with high contrast for the effective recognition. Secondly the character of the stroke-like structure is adequately considered, the stroke filter is applied to get most step-like edges, and at the same time, the text parts are enhanced well. Lastly the missed text pixels in former steps are recalled by local region growing.