Abstract
Pattern Detection (PD) plays an important role in several image processing applications such as feature tracking, object recognition, stereo matching and remote sensing. PD involves two critical aspects: similarity measurement and search strategy. The simplest available PD method finds the best possible coincidence between the images through an exhaustive computation of the Normalized cross-correlation (NCC) values (similarity measurement) for all elements of the source image (search strategy).
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Díaz-Cortés, MA., Cuevas, E., Rojas, R. (2017). States of Matter Algorithm Applied to Pattern Detection. In: Engineering Applications of Soft Computing. Intelligent Systems Reference Library, vol 129. Springer, Cham. https://doi.org/10.1007/978-3-319-57813-2_9
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DOI: https://doi.org/10.1007/978-3-319-57813-2_9
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