Department of Computer Science, School of Computing, National University of Singapore, Singapore.
IEEE Trans Pattern Anal Mach Intell. 2011 Feb;33(2):412-9. doi: 10.1109/TPAMI.2010.166.
In this paper, we propose a method based on the Laplacian in the frequency domain for video text detection. Unlike many other approaches which assume that text is horizontally-oriented, our method is able to handle text of arbitrary orientation. The input image is first filtered with Fourier-Laplacian. K-means clustering is then used to identify candidate text regions based on the maximum difference. The skeleton of each connected component helps to separate the different text strings from each other. Finally, text string straightness and edge density are used for false positive elimination. Experimental results show that the proposed method is able to handle graphics text and scene text of both horizontal and nonhorizontal orientation.
本文提出了一种基于频域拉普拉斯的视频文字检测方法。与许多其他假设文字为水平方向的方法不同，我们的方法能够处理任意方向的文字。输入图像首先经过傅里叶-拉普拉斯滤波。然后使用 K-均值聚类根据最大差值来识别候选文字区域。每个连通分量的骨架有助于将不同的文字字符串彼此分开。最后，文字字符串的直线度和边缘密度用于消除假阳性。实验结果表明，所提出的方法能够处理水平和非水平方向的图形文字和场景文字。
