Please use this identifier to cite or link to this item: https://doi.org/10.1109/TPAMI.2010.166
Title: A Laplacian approach to multi-oriented text detection in video
Authors: Shivakumara, P. 
Phan, T.Q. 
Tan, C.L. 
Keywords: Connected component analysis
frequency domain processing
text detection
text orientation.
Issue Date: 2011
Source: Shivakumara, P., Phan, T.Q., Tan, C.L. (2011). A Laplacian approach to multi-oriented text detection in video. IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (2) : 412-419. ScholarBank@NUS Repository. https://doi.org/10.1109/TPAMI.2010.166
Abstract: AbstractIn 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. © 2011 IEEE.
Source Title: IEEE Transactions on Pattern Analysis and Machine Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/39379
ISSN: 01628828
DOI: 10.1109/TPAMI.2010.166
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