Farsi/Arabic text extraction from video images by corner detection

Video text information plays an important role in semantic-based video analysis, indexing and retrieval. In this paper, we proposed a novel Farsi text detection approach based on intrinsic characteristics of Farsi text lines, which is more robust to complex backgrounds and various font styles. First, by an edge detector operator, all the possible edges in vertical, horizontal, 45 and 135 degrees are extracted. Then, for extracting text strokes, some pre-processing such as dilation and erosion are done according to the font size. Afterward, by finding the edges cross points, corners map is extracted. To discard non-text corners and finding real font size, histogram analysis is done. After finding real font size, input image is rescaled and a new corner map is extracted. Finally, the detected candidate text areas undergo the empirical rules analysis to identify text areas and project profile analysis for verification and text lines extraction. Experimental results demonstrate that the proposed method is robust to font size, font colour, and background complexity.