计算机科学 ›› 2017, Vol. 44 ›› Issue (9): 300-303.doi: 10.11896/j.issn.1002-137X.2017.09.056
王梦迪,张友梅,常发亮
WANG Meng-di, ZHANG You-mei and CHANG Fa-liang
摘要： 文本定位作为文本识别的基础和前提,对图像深层信息的理解至关重要。针对自然场景下的文本定位受光照、复杂背景等因素影响较大的问题,提出了一种基于多方向边缘检测和自适应特征融合的自然场景文本定位方法。该方法首先将自然场景图像进行三通道八方向的边缘检测；然后 通过启发式规则 对得到的边缘图像进行过滤从而提取出备选文本域,进而对备选文本域进行自适应权值的HOG-LBP特征提取与融合；最后采用支持向量机进行特征分类学习,实现文本定位。实验结果表明,该方法能准确定位自然场景图片的文本区域,对光照和复杂背景具有较强的鲁棒性。
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