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Local feature description method based on stationary wavelet transformation and brightness order

A technology of stationary wavelet and local features, which is applied to computer components, character and pattern recognition, instruments, etc., can solve problems such as the inability to guarantee the robustness of descriptors, achieve the invariance of monotonous brightness changes, improve discrimination, and ensure Effects of rotation invariance

Inactive Publication Date: 2017-08-15
STATE GRID ANHUI ELECTRIC POWER CO LTD ANQING POWER SUPPLY CO +2
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Problems solved by technology

However, these methods are all constructed in a single support region, but the single support region is susceptible to image distortion and cannot guarantee the robustness of the descriptor (see the literature "Fan B, Wu F, Hu Z. Rotationally invariant descriptors using intensity order pooling[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(10):2031-2045."), therefore, for the traditional local feature description method, it is necessary to propose a local feature with non-linear brightness invariance descriptor

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  • Local feature description method based on stationary wavelet transformation and brightness order
  • Local feature description method based on stationary wavelet transformation and brightness order
  • Local feature description method based on stationary wavelet transformation and brightness order

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Embodiment Construction

[0048] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0049] Those skilled in the art will understand that unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the word "comprising" used in the description of the present invention refers to the presence of said features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements, components, and / or groups thereof. It will be understoo...

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Abstract

The invention discloses a local feature description method based on stationary wavelet transformation and a brightness order. The method includes the following steps that: the Hessian-Affine operator is adopted to detect an affine covariant region; the stationary wavelet transformation is adopted to decompose the detection region so as to obtain a plurality of support regions of different scales; the brightness order is utilized to divide the support regions, so that sub-regions that do not overlap each other can be obtained; and a three-value mode strategy is utilized to calculate a local feature descriptor under a local rotation invariant coordinate system. According to the method of the invention, the plurality of support regions are obtained through using stationary wavelet decomposition, and therefore, adverse effects caused by image distortion can be effectively reduced; and the brightness order is utilized to divide the support regions, and therefore, the method is invariant to monotonous brightness changes.

Description

technical field [0001] The invention relates to the technical field of computer vision tasks, in particular to a local feature description method based on stationary wavelet transform and brightness sequence. Background technique [0002] The description of image local features is a basic hot issue in the field of computer vision and pattern recognition, and its results have been widely used in target recognition (see the literature "Lowe D G. Distinctive image features from scale-invariant keypoints [J]. International Journal of Computer Vision, 2004, 60(2):91-110."), image retrieval (see the literature "Yang Y, Newsam S. Geographic image retrieval local invariant features [J]. IEEE Transactions on Ge science and RemoteSensing. 2013 ,51(2):818-832."), three-dimensional reconstruction (see the literature "Fu rukawa Y, Ponce J.Accurate, dense, and robust multi-view stereopsis [J]. IEE E Transactions on Pattern Analysis and Machine Intelligence, 2010 ,32(8):136 2-1376."), ima...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/34G06K9/32
CPCG06V10/446G06V10/25G06V10/267
Inventor 房贻广刘武刘群杨可军张骥丁兆硕黄文礼李剑英
Owner STATE GRID ANHUI ELECTRIC POWER CO LTD ANQING POWER SUPPLY CO