Abstract
In this paper, we describe our solution to the marker detection problem in digital images. In order to keep our investigations as general as possible, our approach has not been developed in an application-drivenway. However,we have evaluated the system for the bar code detection problem. To represent the markers, our system uses general feature extraction methods like Hu Moments and the Fourier- Mellin transform which are both invariant to rotation, scaling and translation. For marker classification, Bayes Classifier and Support Vector Machine have been applied. A comprehensive set of experiments performed for our algorithm proved its high robustness for a challenging set of images.
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Feinen, C., Grzegorzek, M., Droege, D., Paulus, D. (2011). A Generic Approach to the Texture Detection Problem in Digital Images. In: Burduk, R., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Computer Recognition Systems 4. Advances in Intelligent and Soft Computing, vol 95. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20320-6_39
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DOI: https://doi.org/10.1007/978-3-642-20320-6_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20319-0
Online ISBN: 978-3-642-20320-6
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