Characteristic extracting and describing method with mirror plate overturning invariability based on SIFT

A feature extraction and feature point technology, applied in the field of image processing, can solve problems such as failure of SIFT feature extraction method

Inactive Publication Date: 2009-07-29
TIANJIN UNIV
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  • Abstract
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Problems solved by technology

[0009] The purpose of the present invention is to provide a kind of problem that can solve the invalidation of SIFT feature e...

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  • Characteristic extracting and describing method with mirror plate overturning invariability based on SIFT
  • Characteristic extracting and describing method with mirror plate overturning invariability based on SIFT
  • Characteristic extracting and describing method with mirror plate overturning invariability based on SIFT

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Embodiment Construction

[0028] In the present invention, the scale change of the input image is performed firstly, and the change is completed through Gaussian convolution. In a series of images of different scales, the extreme point of the gray value of the pixel is searched for each pixel. However, not all extreme points meet the criteria as feature points. Since the feature points need to have certain prominence and robustness, by setting appropriate thresholds for Difference of Gaussian and Hessian matrix , so as to filter the candidate points with low contrast and edge response of feature points respectively. The extreme points left after these two steps of screening are the desired feature points. For these extreme points, after fitting them with a three-dimensional quadratic curve, their precise coordinates and scale information are obtained. The coordinates, scale and other information of the feature points are preserved to provide usable information for the subsequent matching stage.

[002...

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Abstract

The invention pertains to the technical field of image processing and relates to a feature extraction and description method based on SIFT and with invariance in mirror inversion. The method comprises the following steps: (1) a Gaussian kernel convolution process is conducted to an input image; (2) a Gaussian difference process is conducted to the image to detect an extremum point of the image; (3) feature points are selected; (4) locations of the feature points are accurately positioned; (5) a direction parameter of each feature point is determined; (6) summation is conducted to values of gradient modulus respectively taking a main direction as a boundary, at the two sides; and (7) pixel units in a Gaussian weight window are organized to conduct encoding and normalization and further generate description data of the image. The method increases the robustness of feature extraction and description methods to a mirror image and extends the applicable field of computer vision.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to an image feature extraction method. Background technique [0002] Today's computer technology is developing rapidly, and the application fields of computer vision and image retrieval are becoming more and more extensive, which also highlights their importance. Popular 3D reconstruction, object recognition, camera calibration, robot binocular navigation, etc. are all based on computer vision, so reasonably and effectively solving the problems existing in computer vision or improving imperfections can give the computer industry even A huge boost from the scientific community. Computer vision is based on the idea that the computer can simulate human (mammalian) vision to achieve a certain degree of intelligence. Together with image retrieval, it is necessary to extract and analyze the features of the image, so the definition and extraction scheme of image features has a pivo...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06T7/00
CPCG06K9/3208G06V10/242
Inventor 操晓春郭晓杰张钢曲彦龄武琳张炜
Owner TIANJIN UNIV
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