A hybrid framework for efficient and accurate orientation estimation based on single and multiple orientation vector fields
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Legaz Aparicio, Alvar Ginés; Verdú Monedero, Rafael; Morales Sánchez, Juan; Kovalyk, OleksandrÁrea de conocimiento
Teoría de la Señal y las ComunicacionesFecha de publicación
2023-06-14Editorial
ElsevierCita bibliográfica
Legaz-Aparicio, Á.-G., Verdú-Monedero, R., Morales-Sánchez, J., Kovalyk, O. (2023). A hybrid framework for efficient and accurate orientation estimation based on single and multiple orientation vector fields. Expert Systems with Applications, 231, 120776. https://doi.org/10.1016/j.eswa.2023.120776Revisión por pares
siPalabras clave
Orientation estimationSingle orientation
Multiple orientations
Morphological openings
Convolutional neural network
Resumen
This article presents a hybrid framework for efficient and accurate orientation estimation. The proposed scheme combines the single orientation information given by a novel method and the multiple orientation information provided by a bank of linear orientated morphological openings. The single orientations are estimated by means of an energy-minimization Gaussian filtering which solves the drawback related to phase changes of other methods. After describing the formulation of these two approaches for estimating the existing orientations in the pixels of an image, several strategies have been analyzed to fuse and discriminate the information of both orientation vector fields in the resulting hybrid orientation vector field. The objective of the proposed hybrid method is to reduce the computational cost involved in calculating multiple orientations only in those pixels where they exist while maintaining the accuracy provided by the single orientation method in the remaining pixels. To ...
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