Text Extraction from Video and Converted into Video Frame

The goal of this paper is to detect the text from video. With the increasing popularity of practical vision systems and smart phones, text detection in natural scenes becomes a critical yet challenging task. In a society driven by visual information and with the drastic expansion of low-priced cameras, text recognition is nowadays a fast changing field. The goal of this paper is develop a robust algorithm that extracts text from video with cluttered background. We propose a simple but efficient methodology for text detection in video frames. The method is based on the gradient information and edge map selection. In the proposed method we first find the gradient of the image and then enhance the gradient information. We later binarized the enhanced gradient image and select the edges by taking the intersection of the edge map with the binary information of the enhanced gradient image. We use the edge detector for generating the edge map. The selected edges are then morphologically dilated and opened using suitable structuring elements and used for text regions. We then perform the projection profile analysis to identify the boundary of the text region. At the end, we implement a false positive elimination methodology to improve the text detection results. Then we make the video from image frames which contain the detection of text.