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Image matching using rotating filters

Abstract : Nowadays computer vision algorithms can be found abundantly in applications relatedto video surveillance, 3D reconstruction, autonomous vehicles, medical imaging etc. Image/object matching and detection forms an integral step in many of these algorithms.The most common methods for Image/object matching and detection are based on localimage descriptors, where interest points in the image are initially detected, followed byextracting the image features from the neighbourhood of the interest point and finally,constructing the image descriptor. In this thesis, contributions to the field of the imagefeature matching using rotating half filters are presented. Here we follow three approaches:first, by presenting a new low bit-rate descriptor and a cascade matching strategy whichare integrated on a video platform. Secondly, we construct a new local image patch descriptorby embedding the response of rotating half filters in the Histogram of Orientedgradient (HoG) framework and finally by proposing a new approach for descriptor constructionby using second order image statistics. All the three approaches provides aninteresting and promising results by outperforming the state of art descriptors.Key-words: Rotating half filters, local image descriptor, image matching, Histogram of Orientated Gradients (HoG), Difference of Gaussian (DoG).
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https://tel.archives-ouvertes.fr/tel-02102130
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Submitted on : Wednesday, April 17, 2019 - 9:32:07 AM
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  • HAL Id : tel-02102130, version 1

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Darshan Venkatrayappa. Image matching using rotating filters. Data Structures and Algorithms [cs.DS]. Université Montpellier, 2015. English. ⟨NNT : 2015MONTS200⟩. ⟨tel-02102130⟩

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