A Robust Method for TV Logo Tracking in Video Streams
Most broadcast stations rely on TV logos to claim video content ownership or visually distinguish the broadcast from the interrupting commercial block. Detecting and tracking a TV logo is of interest to TV commercial skipping applications and logo-based broadcasting surveillance (abnormal signal is accompanied by logo absence). Pixel-wise difference computing within predetermined logo regions cannot address semi-transparent TV logos well for the blending effects of a logo itself and inconstant background images. Edge-based template matching is weak for semi-transparent ones when incomplete edges appear. In this paper we present a more robust approach to detect and track TV logos in video streams on the basis of multispectral images gradient. Instead of single frame based detection, our approach makes use of the temporal correlation of multiple consecutive frames. Since it is difficult to manually delineate logos of irregular shape, an adaptive threshold is applied to the gradient image in subpixel space to extract the logo mask. TV logo tracking is finally carried out by matching the masked region with a known template. An extensive comparison experiment has shown our proposed algorithm outperforms traditional methods such as frame difference, single frame-based edge matching. Our experimental dataset comes from part of TRECVID2005 news corpus and several Chinese TV channels with challenging TV logos