点击次数：

论文类型：期刊论文

发表时间：2015-03-01

发表刊物：JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY

收录刊物：SCIE、EI、ISTIC、Scopus

卷号：30

期号：2

页面范围：353-363

ISSN号：1000-9000

关键字：text detection; gradient amplitude map; morphological filtering; maximally stable extremal region; graph cuts

摘要：Video text detection is a challenging problem, since video image background is generally complex and its subtitles often have the problems of color bleeding, fuzzy boundaries and low contrast due to video lossy compression and low resolution. In this paper, we propose a robust framework to solve these problems. Firstly, we exploit gradient amplitude map (GAM) to enhance the edge of an input image, which can overcome the problems of color bleeding and fuzzy boundaries. Secondly, a two-direction morphological filtering is developed to filter background noise and enhance the contrast between background and text. Thirdly, maximally stable extremal region (MSER) is applied to detect text regions with two extreme colors, and we use the mean intensity of the regions as the graph cuts' label set, and the Euclidean distance of three channels in HSI color space as the graph cuts smooth term, to get optimal segmentations. Finally, we group them into text lines using the geometric characteristics of the text, and then corner detection, multi-frame verification, and some heuristic rules are used to eliminate non-text regions. We test our scheme with some challenging videos, and the results prove that our text detection framework is more robust than previous methods.