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Megha Khokhra


Text detection, video converted, image frames, caption video, detect text from video, methodology, edge selection


The video image spitted into number of frames, each frame maintains the text. Then the Image is converted into Gray Scale to avoid the text color variation. A single value is corresponding to gray value and detecting the edge. Detecting the edge process is the boundary between two regions with relatively distinct gray-level properties. One is the horizontal direction of the image. Another is the vertical direction of the image. The features to describe text regions are area, saturation, orientation, aspect ratio and position. Then convert into binary image. 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.

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Published in: Volume : 3, Issue : 3
Publication Date: 3/2/2017

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