A novel IPTV framework for automatic TV commercials detection, labeling, recognition and replacement

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Date

2023

Authors

Arsan, Taner
Bulut, Enes Emre
Eren, Berk
Uzgor, Ahmet
Yolcu, Selcuk

Journal Title

Journal ISSN

Volume Title

Publisher

Springer

Open Access Color

Green Open Access

Yes

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Publicly Funded

No
Impulse
Top 10%
Influence
Top 10%
Popularity
Top 10%

Research Projects

Journal Issue

Abstract

Advertisements are one of the most important way for companies to access their customers. In this context, televison commercials are gaining significant importance in many sectors daily, and it is crucial for companies to promote their products in the best way. This creates a big rivalry between companies. From this point of view, we have created an IPTV Framework that can automatically detect commercials of rival companies and replace them with desired commercials for companies to help them highlight their products to their customers. We have benefited from monochrome frames to detect the Livestream commercial block and proposed a fingerprint algorithm to create an automatic commercial database. We can easily recognize the commercials, and we can mask the commercials of rival companies with these techniques. We have tested our algorithm in real-time by streaming a recorded broadcast from a server of a specific TV channel. Experimental results show that our algorithm provides high accuracy in real-time commercial recognition.

Description

Keywords

Commercial detection and recognition, IPTV, Segmentation, Live broadcasting, Video streaming, Segmentation, Commercial replacing, Segmentation, Commercial detection and recognition, Commercial replacing, IPTV, Video streaming, Live broadcasting

Turkish CoHE Thesis Center URL

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Citation

WoS Q

N/A

Scopus Q

Q1
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OpenCitations Citation Count
4

Source

Multimedia Tools and Applications

Volume

82

Issue

6

Start Page

8561

End Page

8579
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Citations

Scopus : 6

Patent Family : 1

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SCOPUS™ Citations

6

checked on Feb 03, 2026

Web of Science™ Citations

1

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Page Views

10

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0.4951672

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