A new approach for video text detection

Text detection is fundamental to video information retrieval and indexing. Existing methods cannot handle well those texts with different contrast or embedded in a complex background. To handle these difficulties, this paper proposes an efficient text detection approach, which is based on invariant features, such as edge strength, edge density, and horizontal distribution. First, it applies edge detection and uses a low threshold to filter out definitely non-text edges. Then, a local threshold is selected to both keep low-contrast text and simplify complex background of high-contrast text. Next, two text-area enhancement operators are proposed to highlight those areas with either high edge strength or high edge density. Finally, coarse-to-fine detection locates text regions efficiently. Experimental results show that this approach is robust for contrast, font-size, font-color, language, and background complexity.