Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Evaluation of Distance Measures for Feature based Image Registration
  using AlexNet   Image registration is a classic problem of computer vision with several
applications across areas like defence, remote sensing, medicine etc. Feature
based image registration methods traditionally used hand-crafted feature
extraction algorithms, which detect key points in an image and describe them
using a region around the point. Such features are matched using a threshold
either on distances or ratio of distances computed between the feature
descriptors. Evolution of deep learning, in particular convolution neural
networks, has enabled researchers to address several problems of vision such as
recognition, tracking, localization etc. Outputs of convolution layers or fully
connected layers of CNN which has been trained for applications like visual
recognition are proved to be effective when used as features in other
applications such as retrieval. In this work, a deep CNN, AlexNet, is used in
the place of handcrafted features for feature extraction in the first stage of
image registration. However, there is a need to identify a suitable distance
measure and a matching method for effective results. Several distance metrics
have been evaluated in the framework of nearest neighbour and nearest neighbour
ratio matching methods using benchmark dataset. Evaluation is done by comparing
matching and registration performance using metrics computed from ground truth.
  Keywords: Distance measures; deep learning; feature detection; feature
descriptor; image matching

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The categories of this paper are: hep-ex
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The categories of this paper are: astro-ph
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The categories of this paper are: math-ph
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The categories of this paper are: q-bio
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The categories of this paper are: funct-an
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The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-ex
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The categories of this paper are: ao-sci
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The categories of this paper are: hep-ph
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The categories of this paper are: physics
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The categories of this paper are: hep-th
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The categories of this paper are: nucl-th
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The categories of this paper are: cmp-lg
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The categories of this paper are: comp-gas