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A 3D point cloud auricle recognition method that can improve recognition accuracy and efficiency

A recognition accuracy, 3D point cloud technology, applied in biometric recognition, 3D object recognition, character and pattern recognition, etc., can solve problems such as inability to accurately locate, directly apply 3D point cloud auricle recognition, and require manual measurement.

Inactive Publication Date: 2019-04-05
LIAONING NORMAL UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method not only requires manual measurement of the size of each part on the 2D image, which cannot be accurately positioned, but also cannot be directly applied to the 3D point cloud auricle recognition.

Method used

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  • A 3D point cloud auricle recognition method that can improve recognition accuracy and efficiency
  • A 3D point cloud auricle recognition method that can improve recognition accuracy and efficiency
  • A 3D point cloud auricle recognition method that can improve recognition accuracy and efficiency

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Embodiment Construction

[0052] The specific embodiment of the present invention is performed on the UND three-dimensional auricle database, which contains 1800 three-dimensional auricles from 415 people.

[0053] Specifically follow the steps below:

[0054] a. Based on PCA and SVD decomposition, perform normalized preprocessing on the position and attitude of the 3D auricle point cloud model:

[0055] Due to the large construction time span of the 3D auricle data set, the same auricle data acquired at different acquisition times will be affected by factors such as the distance and angle between the acquired auricle and the acquisition device. The auricle model in the auricle database is used for normalized preprocessing.

[0056] Specific steps are as follows:

[0057] Set the vertex set of any 3D auricle point cloud model ,but V of The order geometric moment is:

[0058]

[0059] but V The three first-order geometric moments and six second-order geometric moments of are:

[0060]

...

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Abstract

The invention discloses a three-dimensional point cloud auricle recognition method capable of improving recognition accuracy and efficiency, which is characterized in that it is carried out according to the following steps: based on PCA and SVD decomposition, the position and attitude of the three-dimensional auricle point cloud model are normalized and pre-calculated Processing; based on the Iannarelli classification system, four local feature regions of the 3D auricle point cloud model were extracted; the Sparse ICP algorithm was used to match the local feature regions of the 3D auricle point cloud model to obtain all initial matching point pairs; based on SVD Solve the rotation transformation between matching point pairs R and translation transformation T , minimize the error function E , until the distance error between the models reaches the minimum value, the optimal registration is obtained.

Description

technical field [0001] The invention relates to a three-dimensional point cloud auricle recognition method, in particular to a three-dimensional point cloud auricle recognition method that can improve recognition accuracy and efficiency. Background technique [0002] The auricle is composed of helix, antihelix, scaphoid, triangular fossa, tragus, antitragus, earlobe, etc. It has a remarkable undulating shape and unique three-dimensional shape characteristics, and is more universal, unique, permanent and easy Acquisition. Auricle recognition technology is an emerging biometric technology in recent years. It mainly uses three-dimensional shape features such as gullies and twists in the shape of the human ear for recognition. It is a permanent biomarker just like human biological characteristics such as palms, fingerprints, irises, and DNA. Compared with the two-dimensional pinna recognition technology, the three-dimensional pinna pose is less affected by external factors such...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/52
CPCG06V20/653G06V40/10G06V10/42
Inventor 孙晓鹏马晓萌王璐王森
Owner LIAONING NORMAL UNIVERSITY
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