|Title:||Two-steps perceptual important points estimator in 8-connected curves from handwritten signature||Authors:||Ferrer, Miguel A.
|UNESCO Clasification:||1203 Ciencia de los ordenadores||Keywords:||Handwritting segmentation
High curvature points
Perceptual important points estimation
|Issue Date:||2018||Journal:||Proceedings Of The 2017 Seventh International Conference On Image Processing Theory, Tools And Applications (Ipta 2017)||Conference:||7th International Conference on Image Processing Theory, Tools and Applications, IPTA 2017||Abstract:||Estimating the salient points in 8-connected curves from handwritten signature is a difficult task due to their relation to the writer neuromotor system. This paper faces up this topic proposing a two-steps perceptual important points estimation method: the first step estimates the sharper salient points by a curvature analysis at multiple scales, whereas the second step estimates the smoother salient points relying on circular shapes between estimated salient points in step one. In this approach, both sharper and smoother salient points represent the set of perceptual important points in an eight connected signature trajectory. Our validations, conducted on 2112 signatures from 132 users of the BiosecurID database, are focused on i) evaluating the number of estimated perceptual important points; ii) evaluating their locations in the trajectory and iii) evaluating the accuracy of the estimated duration of the signatures from the number of perceptual important points. The obtained results are encouraging for new developments in handwriting analysis based on this procedure.||URI:||http://hdl.handle.net/10553/42042||ISBN:||9781538618417||ISSN:||2154-512X||DOI:||10.1109/IPTA.2017.8310077||Source:||Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), Montreal, QC, 2017, pp. 1-5|
|Appears in Collections:||Actas de congresos|
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.