Video text detection based on filters and edge features

Text detection plays a vital role in retrieving and browsing video data efficiently and accurately. In this paper, we propose a method for detecting both graphics and scene text in video images by proposing initial text block identification, text portion segmentation and new edge features for false positive elimination. The heuristic rules based on filters and edge analysis are formed to identify the initial text block and to segment the complete text portion from the image. The new edge features such as straightness and cursiveness are explored to eliminate false positives. To evaluate the performance of the proposed method, we introduce misdetection rate and processing time in addition to detection rate and false positive rate. The experimental results show that the proposed method outperforms existing methods in terms of the above metrics.