We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the ccentral pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance.
As the rapid development of intelligent TV, TV logo recognition plays an important role in the applications of video analysis and video retrieval. This paper utilizes the luminance variance information to extract logo mask along a set of consecutive frames. An effect and efficient method, projection distribution histogram intersection (PDHI) is proposed to calculate the similarity of two logos. Experiments are conducted on a large database collected by ourselves, including 57 challenging standard definition (SD) and 10 high definition (HD) TV channels, the results are promising.
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