26 May 2011 Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition
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Abstract
Hypercomplex approaches are seeing increased application to signal and image processing problems. The use of multicomponent hypercomplex numbers, such as quaternions, enables the simultaneous co-processing of multiple signal or image components. This joint processing capability can provide improved exploitation of the information contained in the data, thereby leading to improved performance in detection and recognition problems. In this paper, we apply hypercomplex processing techniques to the logo image recognition problem. Specifically, we develop an image matcher by generalizing classical phase correlation to the biquaternion case. We further incorporate biquaternion Fourier domain alpha-rooting enhancement to create Alpha-Rooted Biquaternion Phase Correlation (ARBPC). We present the mathematical properties which justify use of ARBPC as an image matcher. We present numerical performance results of a logo verification problem using real-world logo data, demonstrating the performance improvement obtained using the hypercomplex approach. We compare results of the hypercomplex approach to standard multi-template matching approaches.
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Stephen DelMarco, "Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition", Proc. SPIE 8063, Mobile Multimedia/Image Processing, Security, and Applications 2011, 80630D (26 May 2011); doi: 10.1117/12.883302; https://doi.org/10.1117/12.883302
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