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Improved SURF fast matching method

A matching method, fast technology, applied in image analysis, instrumentation, calculation, etc., can solve problems such as reduction and high accuracy

Inactive Publication Date: 2013-12-04
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that the classic SURF algorithm is still too time-consuming and the accuracy rate is reduced, and an improved SURF fast matching method is provided, which can significantly improve the speed and accuracy of the classic SURF algorithm

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Embodiment Construction

[0030] The present invention will be further described below in conjunction with the accompanying drawings and embodiments, but is not limited thereto.

[0031] Example:

[0032] Embodiment 1 of the present invention such as figure 1As shown, an improved SURF fast matching method, the steps are as follows:

[0033] 1) Find the integral image of the initial image and the determinant of the Hessian matrix

[0034] Traverse the initial image that needs to be matched to obtain the integral image of the initial image, and obtain the determinant of the Hessian matrix of each point on the image;

[0035] 2) Establish scale space pyramid and locate feature points

[0036] In order to make the SURF algorithm scale-invariant, a scale-space pyramid must be established to keep the size of the image constant, and the scale-image pyramid is established by changing the template size of the box filter. The specific construction method is: the image scale-space pyramid is divided into four ...

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Abstract

The invention discloses an improved SURF fast matching method, and belongs to the technical field of digital image processing. The improved SURF fast matching method comprises the steps that an original image and an integral image are converted and detection of feature points is conducted through a Hessian matrix; the feature points, obtained by using a scale space, are scale-invariant; positioning of the primary direction of the feature points are conducted by calculating the maximum value responded to a Harr small wave; the feature points are classified through an improved feature-point classifying method and feature describing is conducted on the feature points and a 66 dimension feature vector is formed; matching of feature points in a set is conducted finally. According to the improved SURF fast matching method, selected feature points in one image are not needed to be matched with all the feature points in another image, both matching speed and accuracy are greatly improved, and the improved SURF fast matching method has the advantages that the improved SURF fast matching method has properties, such as scale invariance and translation rotating resistance, of classic SURF (Speeded Up Robust Features).

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to an improved SURF fast matching method. Background technique [0002] In image processing and machine vision, the description and detection of local image features can be used to help identify objects, so it is of great significance to the extraction of local features of objects. [0003] Herbert Bay et al. proposed the SURF algorithm in the article "SURF: Speeded Up Robust Features [J]. Computer Vision and Image Understanding (CVIU), 2008, 110(3): 346-359." in 2006. The SURF algorithm is A local feature description algorithm with advantages such as scale invariance. But in the process of target recognition based on vision, the most concerned issues are the accuracy of recognition and whether it can be processed in real time. Since the feature matching comparison of the SURF algorithm needs to match each selected feature point on one image with all the feature p...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 杨明强韩峰贲晛烨
Owner SHANDONG UNIV
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