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Proceedings Paper

Spatial detection of tv channel logos as outliers from the content
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Paper Abstract

This paper proposes a purely image-based TV channel logo detection algorithm that can detect logos independently from their motion and transparency features. The proposed algorithm can robustly detect any type of logos, such as transparent and animated, without requiring any temporal constraints whereas known methods have to wait for the occurrence of large motion in the scene and assume stationary logos. The algorithm models logo pixels as outliers from the actual scene content that is represented by multiple 3-D histograms in the YCBCR space. We use four scene histograms corresponding to each of the four corners because the content characteristics change from one image corner to another. A further novelty of the proposed algorithm is that we define image corners and the areas where we compute the scene histograms by a cinematic technique called Golden Section Rule that is used by professionals. The robustness of the proposed algorithm is demonstrated over a dataset of representative TV content.

Paper Details

Date Published: 19 January 2006
PDF: 8 pages
Proc. SPIE 6077, Visual Communications and Image Processing 2006, 60770X (19 January 2006); doi: 10.1117/12.642739
Show Author Affiliations
Ahmet Ekin, Philips Research (Netherlands)
Ralph Braspenning, Philips Research (Netherlands)

Published in SPIE Proceedings Vol. 6077:
Visual Communications and Image Processing 2006
John G. Apostolopoulos; Amir Said, Editor(s)

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