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Method for extracting maximally stable extremal region with scale invariance

A technique for stabilizing extreme value regions and scale invariance. It is used in instruments, character and pattern recognition, computer components, etc., and can solve problems affecting the stability of affine invariant regions and boundary changes.

Active Publication Date: 2014-11-19
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

Since MSER is extracted from a single-scale image, when the image scale changes greatly, the blurring of the image will change the boundary of the most stable extremum region, thus affecting the stability of the affine invariant region

Method used

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  • Method for extracting maximally stable extremal region with scale invariance
  • Method for extracting maximally stable extremal region with scale invariance
  • Method for extracting maximally stable extremal region with scale invariance

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Embodiment Construction

[0029] Below in conjunction with accompanying drawing and embodiment data, above-mentioned method is described in detail:

[0030] Such as figure 1 As shown, a method for extracting the most stable extremum region with scale invariance includes the following steps:

[0031] The first step is to detect MSER in the original image according to the MSER implementation algorithm proposed by Murphy et al. (This step uses the existing algorithm, the detailed process will not be repeated, only the definition of MSER is as follows:)

[0032] The grayscale image I can be defined as a mapping from 2-dimensional pixel coordinates to the grayscale value S. The limit region ER in the image I is a connected region and satisfies the following conditions:

[0033] ∀ p ∈ ER , ∀ q ∈ C ( ER ) → I ( p ...

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Abstract

The invention discloses a method for extracting a maximally stable extremal region with scale invariance. The method includes the steps that firstly, an initial maximally stable extremal region is detected in an original image through a maximally stable extremal region algorithm; then a scale pyramid of the initial maximally stable extremal region is built through M-scale wavelet transform, characteristic points with the scale invariance are determined in the scale pyramid according to energy operators of an M-scale wavelet transform coefficient, extremal regions corresponding to the characteristic points are obtained from all layers of images of the scale pyramid of the maximally stable extremal region, and the maximally stable extremal region with the scale invariance is extracted through the stability indexes of the extremal region in a multi-scale space; finally, the maximally stable extremal region with the scale invariance is adjusted to be in an oval shape, and the final maximally stable extremal region with the scale invariance is obtained. According to the method for extracting the maximally stable extremal region with the scale invariance, the scale invariance and the maximally stable extremal region are combined, the maximally stable extremal region is extracted, and full affine invariance is achieved.

Description

Technical field: [0001] The invention relates to the extraction of the invariant feature area of ​​the digital image, especially the extraction method of the most stable extremum area with scale invariance. Background technique: [0002] Detecting feature regions from images has always been one of the key research issues in the field of computer vision. In recent years, image affine-invariant feature regions based on local regions have attracted more and more attention, and have been successfully applied in many fields such as object recognition, image retrieval, robot autonomous navigation and scene understanding, and object image classification. [0003] Typical local feature region detection algorithms include: the scale invariant feature point SIFT (scale invariant feature transform) proposed by Lowe, the affine invariant feature point based on multi-scale Harris corners proposed by Mikolajczyk and Schmid, the Kadir et al. The affine invariant significant region (AISR) ...

Claims

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Application Information

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IPC IPC(8): G06K9/46
Inventor 张政刘煜谭树人张茂军周韬
Owner NAT UNIV OF DEFENSE TECH
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