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Digital Object Identifier (DOI) : 10.14569/IJACSA.2018.090453
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 4, 2018.
Abstract: A novel framework is presented that can segment semantic videos and detect commercials (ads) in a broadcasted TV transmission. The proposed technique combines SURF features and color Histogram in a weighted combination framework resulting in detecting individual TV ads from the transmission after segmenting semantic videos. Thus, better results are achieved. The proposed framework is designed for TV transmissions those who do not use black frame technique between the ad and non-ad part of the transmission and is commonly used in Pakistani TV channels transmission. The television transmission standards in Pakistan are different from those that are used in other countries of the world. The framework used unsupervised technique to segment the semantic videos.
Waseemullah , Najeed Ahmed Khan and Umair Amin, “Unsupervised Ads Detection in TV Transmissions” International Journal of Advanced Computer Science and Applications(IJACSA), 9(4), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090453
@article{2018,
title = {Unsupervised Ads Detection in TV Transmissions},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090453},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090453},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {4},
author = {Waseemullah and Najeed Ahmed Khan and Umair Amin}
}