Proceedings of Sixth International Conference on Document Analysis and Recognition
DOI: 10.1109/icdar.2001.953805
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An efficient correlation computation method for binary images based on matrix factorisation

Abstract: A novel algorithm for complexity reduction in binary image processing, namely for computation of correlation between image and object template is proposed. This algorithm is based on direct Computation of vector-matrix multiplication with utilisation of binary matrix factorisation approach. Comparison with other algorithms is givenand it is shown that our approach allows to reduce time and complexily of this task.

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Cited by 2 publications
(1 citation statement)
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“…Robust and easier to interpret, the Normalized Gradient Field (NGF) measures a normalized distance between the gradients of the images to be registered [ 34 , 35 ]. Some works proposed calculating the similarity measures from binary data, arguing that the registration process is, in this way, accelerated [ 36 , 37 , 38 , 39 ]. These three similarity measures were used for comparison in the registration algorithm.…”
Section: Methodsmentioning
confidence: 99%
“…Robust and easier to interpret, the Normalized Gradient Field (NGF) measures a normalized distance between the gradients of the images to be registered [ 34 , 35 ]. Some works proposed calculating the similarity measures from binary data, arguing that the registration process is, in this way, accelerated [ 36 , 37 , 38 , 39 ]. These three similarity measures were used for comparison in the registration algorithm.…”
Section: Methodsmentioning
confidence: 99%