A General Framework for Partial to Full Image Registration
- URL: http://arxiv.org/abs/2207.06387v1
- Date: Wed, 13 Jul 2022 17:44:49 GMT
- Title: A General Framework for Partial to Full Image Registration
- Authors: Carlos Francisco Moreno-Garcia, Francesc Serratosa
- Abstract summary: In some applications (such as forensic biometrics, satellite photography or outdoor scene identification) classical image registration systems fail due to one of the images compared represents a tiny piece of the other image.
We present a rotation invariant registration method that explicitly considers that the image to be matched is a small piece of a larger image.
- Score: 11.127510588502233
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Image registration is a research field in which images must be compared and
aligned independently of the point of view or camera characteristics. In some
applications (such as forensic biometrics, satellite photography or outdoor
scene identification) classical image registration systems fail due to one of
the images compared represents a tiny piece of the other image. For instance,
in forensics palmprint recognition, it is usual to find only a small piece of
the palmprint, but in the database, the whole palmprint has been enrolled. The
main reason of the poor behaviour of classical image registration methods is
the gap between the amounts of salient points of both images, which is related
to the number of points to be considered as outliers. Usually, the difficulty
of finding a good match increases when the image that represents the tiny part
of the scene has been drastically rotated. Again, in the case of palmprint
forensics, it is difficult to decide a priori the orientation of the found tiny
palmprint image. We present a rotation invariant registration method that
explicitly considers that the image to be matched is a small piece of a larger
image. We have experimentally validated our method in two different scenarios;
palmprint identification and outdoor image registration.
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