Publication Date:
2016-12-01
Description:
Computational underwater image analysis is developing
into a mature field of research, with an increasing number
of companies, academic groups and researchers showing interest
in it. While on the one hand, the basic question is addressed by
many groups, how algorithms can be applied to automatically
detect and classify objects of interest (OOI) in underwater image
footage, on the other hand the questions for efficiency and
performance, i.e. the time a computer (or a compute cluster)
needs to perform this task, has received much attention yet.
In this paper we will show, how nowadays methods for high
performance computing like parallelization and GPU computing
via CUDA (Compute Unified Device Architecture) can be used to
achieve both, image enhancement and segmentation in less than
0:2 sec per image (4224 x 2376 pixel) on average, which paves
the way to real time online applications.
Type:
Book chapter
,
NonPeerReviewed
Format:
text
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