Hybrid approach for Farsi/Arabic text detection and localisation in video frames

Video text detection plays an important role in semantic-based video analysis. In this study, a new Farsi/Arabic text detection and localisation approach is proposed. First, with the help of edge extraction, artificial corners are obtained and font size estimation is performed. Second, by combining discrete cosine transform coefficients, texture intensity picture is created. Afterwards, a new Local Binary Pattern (LBP) picture is introduced to describe the obtained texture pattern. The input image is then divided into macro blocks and some features are extracted from them and fed into Support Vector Machone (SVM) classifier to categorize them into text and non-text groups. Finally, the candidate text blocks undergo project profile analysis and empirical rules for text localisation. Experimental results demonstrate that the proposed hybrid approach can be used as an automatic text detection system, which is robust to font size, font colour and background complexity.