A Novel Arbitrary-Oriented Multilingual Text Detection in Images/Video

Text in images and videos plays a vital role to understand the events. The textual information is a prominent source and semantic information of a particular content of the respective image or video. Text detection is a primary stage for text recognition and text understanding. Still, text detection process is a challenging and interesting research work in the field of computer vision due to illumination, alignments, complex background and variation size, color, fonts of the text. The multilingual text consists of different geometrical structures of languages. In this paper, a simple and yet effective approach is presented to detect the text from arbitrary oriented multilingual images/video. The proposed method is based on Laplacian of Gaussian information and full connected component analysis. The proposed method is evaluated on four datasets such as Hua’s dataset, arbitrarily oriented dataset, Multi-script Robust Reading Competition (MRRC) dataset and MSRA dataset with performance measures precision, recall and f-measure. The results show that the proposed method is promising and encouraging.