Scene matching region selecting method based on regression learning

A technology of scene matching and matching area, applied in the field of scene matching and navigation, can solve the problem of poor adaptability of scene matching area, and achieve the effect of reducing the amount of calculation, saving time, and ensuring uniqueness

Inactive Publication Date: 2015-01-07
中国人民解放军63620部队
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Problems solved by technology

[0006] The present invention needs to provide a method for selecting a scene matching area to solve the problems in the prior art that when selecting a scene matching area, it is necessary to set a classification threshold to realize the classification of the training set and the poor adaptability of the selected scene matching area, so as to realize the rapid selection of the scene matching area. select

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  • Scene matching region selecting method based on regression learning
  • Scene matching region selecting method based on regression learning
  • Scene matching region selecting method based on regression learning

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Embodiment Construction

[0037] Below in conjunction with the examples, the specific implementation of the present invention will be further described in detail.

[0038] The present invention provides a method for selecting a scene matching area based on regression learning, comprising the following steps:

[0039] S1. Select a plurality of image adaptation features to form an image feature vector, and obtain the image feature vector of the training image;

[0040] Preferably, the multiple image adaptation features include 10 spatial domain image adaptability features and 2 frequency domain image adaptation features, specifically:

[0041] The spatial domain image adaptability features include full image standard deviation, absolute value roughness, edge density, edge density standard deviation, zero crossing density, image information entropy, fractal dimension of fractal Brownian model, minimum local standard deviation, Frieden gray degree entropy and gradient intensity mean value; the frequency-d...

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Abstract

The invention relates to the technical field of scene matching navigation, and provides a scene matching region selecting method based on regression learning. The method includes the steps of firstly, defining ten empty domain image suitability characteristics and two frequency domain image suitability characteristics, combining the twelve suitability characteristics to form an image characteristic vector, training the image characteristic vector through a least-square support vector regression machine, and constructing a regression model between the image characteristic vector and the image matching probability; secondly, predicting a to-be-extracted image through the least-square support vector regression machine to obtain candidate matching regions, and rapidly evaluating the uniqueness of the region through a frequency domain self-correlation tool to obtain a final scene matching region. By means of the method, a small number of candidate matching regions which are rich in texture and highlighted in structure can be rapidly found in the input image, uniqueness verification can be conducted on the candidate matching regions, the calculation amount is greatly reduced, and the method has wide prospects.

Description

technical field [0001] The invention relates to the technical field of scene matching and navigation, in particular to a method for selecting a scene matching area based on regression learning. Background technique [0002] Scene matching area selection is one of the key technologies of scene matching, which refers to selecting a scene image with a large amount of information, obvious features, good adaptability, and a size that meets the requirements of the reference map on the predetermined flight path according to certain requirements or criteria. Techniques for Matching Baseline Maps. [0003] In the prior art, the selection of the scene matching area mainly adopts the autocorrelation method, which needs to first traverse and calculate the autocorrelation surface of all the candidate areas of the image, and then select the area according to some characteristics of the surface. This method has a large amount of calculation, and it usually takes several hours or even days...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/22G06F18/214
Inventor 涂国勇周韶斌伞景辉李壮李伟建王国华李昕磊王震马向斌
Owner 中国人民解放军63620部队
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