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Three-dimensional auricle point cloud shape feature matching method based on IsoRank algorithm

A technology of shape features and matching methods, applied in computing, image data processing, 3D modeling, etc., to achieve the effect of improving registration accuracy and matching efficiency and reducing the amount of data

Inactive Publication Date: 2014-05-21
LIAONING NORMAL UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, so far, there is no relevant report on solving the shape feature matching problem of 3D auricle point cloud based on IsoRank algorithm

Method used

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  • Three-dimensional auricle point cloud shape feature matching method based on IsoRank algorithm
  • Three-dimensional auricle point cloud shape feature matching method based on IsoRank algorithm
  • Three-dimensional auricle point cloud shape feature matching method based on IsoRank algorithm

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Embodiment Construction

[0016] a. Based on the PCA method, analyze the shape features in the local neighborhood sphere of the auricle point cloud, and extract the shape key points of the auricle point cloud;

[0017] For any auricle point cloud M, randomly select a data point p on M, if the distance d between point p and the edge of the auricle is greater than a given threshold δ (here let δ=r+10mm), point p is called a seed point , denoted as fp; take any seed point fp as the center, make a ball with r as the radius, and perform principal component analysis (PCA, Principal Component Analysis) on all the data points in the ball to obtain the eigenvector matrix M evec and the eigenvalue matrix M eval ;Project all points in the sphere onto the eigenvectors corresponding to the two larger eigenvalues, remember the difference between the maximum value and minimum value projected in the two directions is dx and dy respectively, let t=|dx-dy |, if t is greater than the specified threshold, then set the se...

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Abstract

The invention discloses a three-dimensional auricle point cloud shape feature matching method based on an IsoRank algorithm. The method includes the steps: analyzing shape features in neighborhood balls of auricle point clouds based on a PCA (principal component analysis) method and extracting shape key points of the auricle point clouds; triangulating a key point set based on a Delaunay method and building a three-dimensional grid chart of an auricle key point set based on a mapping relation; constructing an auricle key point bidirectional graph based on the edge weight of the three-dimensional grid chart of the auricle key point set, and seeking maximum whole matching of the three-dimensional grid chart and the auricle key point bidirectional graph by the aid of the IsoRank algorithm. The method is low in time complexity and high in matching precision and matching efficiency.

Description

technical field [0001] The invention relates to a three-dimensional auricle shape matching technology, in particular to a three-dimensional auricle point cloud shape feature matching method based on an IsoRank algorithm that can effectively improve registration efficiency and accuracy. Background technique [0002] As a newcomer in the field of biometric identification, the auricle has received more and more attention. The auricle has rich characteristic structures, and its protruding helix, tragus, and earlobe, as well as the sunken ear socket, scaphoid, and ear cavity, all bring troubles to the local matching of the auricle. [0003] In the past, most recognition methods based on three-dimensional pinna information used the ICP (Iterative Closest Point) algorithm and the deformation of the ICP algorithm. For example, the contour matching method for 3D human ear recognition proposed by Chen et al. in 2005 mainly uses a two-step ICP method for auricle matching. The first st...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/00G06T7/00
Inventor 孙晓鹏韩枫
Owner LIAONING NORMAL UNIVERSITY