Authors:
Ignacio de Loyola Páez-Ubieta
;
Daniel Frau-Alfaro
and
Santiago Puente
Affiliation:
AUtomatics, RObotics, and Artificial Vision (AUROVA) Lab, University Institute for Computer Research (IUII), University of Alicante, Crta. San Vicente s/n, San Vicente del Raspeig, E-03690, Alicante, Spain
Keyword(s):
Multispectral Imagery, Labeling, Phase Correlation, Label Transfer, Pills.
Abstract:
In this work, a novel approach for the automated transfer of Bounding Box (BB) and mask labels across different channels on multilens cameras is presented. For that purpose, the proposed method combines the well-known phase correlation method with a refinement process. In the initial step, images are aligned by localising the peak of intensity obtained in the spatial domain after performing the cross-correlation process in the frequency domain. The second step consists of obtaining the optimal transformation through an iterative process that maximises the IoU (Intersection over Union) metric. The results show that the proposed method enables the transfer of labels across different lenses on a camera with an accuracy of over 90% in the majority of cases, with a processing time of just 65 ms. Once the transformations have been obtained, artificial RGB images are generated for labelling purposes, with the objective of transferring this information into each of the other lenses. This wor
k will facilitate the use of this type of camera in a wider range of fields, beyond those of satellite or medical imagery, thereby enabling the labelling of even invisible objects in the visible spectrum.
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