Method of rapidly extracting area of interest of palm print

A technology of region of interest and extraction method, which is applied in the field of palmprint region of interest extraction, can solve the problems of slow extraction speed, low algorithm robustness, high complexity of parameter adjustment, etc., and achieve fast and accurate extraction effect

Active Publication Date: 2016-06-22
SHENZHEN INST OF FUTURE MEDIA TECH +1
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AI Technical Summary

Problems solved by technology

[0007] The main purpose of the present invention is to propose a method for quickly and accurately extracting the region of interest of a high-resolution palmprint image, so as to solve the problems caused by setting distance and tangent circle parameter extraction in existing methods: slow extraction speed and complicated parameter adjustment The problem of high precision and low robustness of the algorithm can be quickly and accurately extracted to the area of ​​interest of the palmprint

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  • Method of rapidly extracting area of interest of palm print
  • Method of rapidly extracting area of interest of palm print
  • Method of rapidly extracting area of interest of palm print

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Embodiment Construction

[0022] The present invention will be further described below with reference to the accompanying drawings and in combination with preferred embodiments.

[0023] The specific implementation example of the present invention provides a detailed process of building a convolutional neural network and extracting palmprint regions of interest, such as figure 1 As shown, it includes the following steps: mark the valley points between the fingers of the training samples, train the convolutional neural network for extracting the valley points between the fingers of the low-resolution palmprint image, extract the key points and map them to the high-resolution palmprint to extract the key points as For the subgraph in the center, select the secondary extraction method. When the flag is selected as 1, train a new convolutional neural network to quickly extract the inter-finger valley points of the sub-graph. When the flag is selected as 0, use the local tangent method to quickly extract the...

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Abstract

The invention discloses a method of rapidly positioning an area of interest of a palm print. The method comprises five processes of marking valley points among fingers of a training sample; training a convolution nerve network used for detecting valley points among fingers of a low-resolution palm print; extracting a key point among fingers of the low-resolution palm print and acquiring a subgraph which takes the key point as a center in a high-resolution palm print; aiming at the subgraph, rapidly extracting an accurate valley point among fingers and positioning the area of interest of the palm print according to the valley point. During a process of training the convolution nerve network, the training sample is amplified and then is input into a network for several times in batches, and a learning rate is gradually reduced along with increase of the batches so as to increase a training speed during the training. During an extraction process, the key point among the fingers of the low-resolution palm print is firstly positioned, and then the subgraph taking the key point as the center is acquired in the high-resolution palm print through mapping, the convolution nerve network or a tangent method is used in the subgraph to carry out local search so as to rapidly extract the valley points among the fingers, and finally, the points are used to accurately position the area of interest of the palm print.

Description

technical field [0001] The invention relates to palmprint recognition in the technical field of biometrics, in particular to a method for extracting an area of ​​interest from palmprints. Background technique [0002] Human biometrics is a general term for various physiological and behavioral characteristics inherent in human beings. These characteristics are unique and invariant. Compared with traditional identity authentication methods, biometrics are safer and more convenient. Physiological characteristics are mostly congenital characteristics, which do not change with external conditions and subjective wishes, such as fingerprints, palm prints, and veins; behavioral characteristics are acquired behavior habits, such as handwriting and gait. [0003] Among them, palmprint recognition is one of the more popular biometric identification directions in recent years. Compared with the more mature fingerprint recognition, palmprint has a larger effective area and richer texture...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/32G06K9/00
CPCG06V40/12G06V10/25G06F18/214
Inventor 郭振华鲍鲜杰张林
Owner SHENZHEN INST OF FUTURE MEDIA TECH
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