【摘要】 在定位和验证的两级框架下提出了一种新的视频文字定位算法.在定位模块中,充分利用字符的笔画属性,引入对字符区域有很强的响应的笔画算子;经笔画提取,密度过滤,区域分解得候选文本行.在验证模块中,提取对文字有较强鉴别能力的边缘方向直方图特征,使用Adaboost算法训练的分类器对候选文本行进行筛选.实验结果表明,该算法具有较强的鲁棒性,在不同类型的视频帧中都能得到较好的定位结果.更多还原

【Abstract】 This paper proposes a new video text localization algorithm in a localization-to-verification framework.In the localization module,to take full advantage of character stroke attribute,the algorithm introduces a stroke operator which has a strong response to text regions;subsequently,it performs strokes extraction,stroke density filtration and region decomposition to obtain candidate text boxes.In verification module,the algorithm extracts edge oriental histogram features,which have strong discriminabilities for text and non-text,then the Adaboost classifier is used to verify candidate text boxes.Experimental results demonstrate that the proposed algorithm has strong robustness and is capable of obtaining relatively good localization results in various types of video frames.更多还原