Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICPR.2010.40
Title: A new symmetry based on proximity of wavelet-moments for text frame classification in video
Authors: Shivakumara, P. 
Dutta, A.
Tan, C.L. 
Pal, U.
Issue Date: 2010
Source: Shivakumara, P.,Dutta, A.,Tan, C.L.,Pal, U. (2010). A new symmetry based on proximity of wavelet-moments for text frame classification in video. Proceedings - International Conference on Pattern Recognition : 129-132. ScholarBank@NUS Repository. https://doi.org/10.1109/ICPR.2010.40
Abstract: This paper proposes the use of a new symmetry property based on proximity of the median moments in the wavelet domain. The method divides a given frame into 16 equally sized blocks to classify the true text frame. The average of high frequency subbands of a block is used for computing median moments to brighten the text pixel in a block of video frame. Then K-means clustering with K=2 is applied on the median moments of the block to classify it as a probable text block. For classified blocks, average wavelet median moments are computed for a sliding window. We introduce Max-Min cluster to classify the probable text pixel in each probable text block. The four quadrants are formed from the centroid of the probable text pixels. The new concept called symmetry is introduced to identify the true text block based on proximity between probable text pixels in each quadrant. If the frame produces at least one true text block, it is considered as a text frame otherwise a non-text frame. The method is tested on three datasets to evaluate the robustness of the method in classification of text frames in terms of recall and precision. © 2010 IEEE.
Source Title: Proceedings - International Conference on Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/41710
ISBN: 9780769541099
ISSN: 10514651
DOI: 10.1109/ICPR.2010.40
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

39
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.