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Palm and key point detection method, device and terminal device thereof

A detection method and key point technology, applied in the field of biometrics, can solve problems such as low accuracy rate and slow detection speed, achieve the effect of improving accuracy rate, improving detection speed, and solving low accuracy rate

Active Publication Date: 2019-02-15
厦门熵基科技有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In view of this, the embodiment of the present application provides a palm and its key point detection method, device and terminal equipment to solve the problem of low accuracy and slow detection speed of the existing palm and its key point detection method

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  • Palm and key point detection method, device and terminal device thereof
  • Palm and key point detection method, device and terminal device thereof
  • Palm and key point detection method, device and terminal device thereof

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Embodiment 1

[0040] The following describes a palm and its key point detection method provided in Embodiment 1 of the present application, please refer to the attached figure 1 , a method for detecting palms and key points thereof in the embodiment of the present application includes:

[0041]Step S101. Scale the image to be detected to the first image size and input it into the trained first neural network to obtain the probability of the first palm image of the image to be detected, and determine whether the probability of the first palm image is greater than the first probability threshold .

[0042] Among them, the neural network is an algorithmic mathematical model that imitates the behavior characteristics of animal neural networks and performs distributed parallel information processing. This network relies on the complexity of the system and adjusts the interconnection relationship between a large number of internal nodes to achieve information processing. the goal of.

[0043] T...

Embodiment 2

[0084] Embodiment 2 of the present application provides a palm and its key point detection device. For the convenience of description, only the parts related to the present application are shown, such as Figure 7 As shown, the palm and its key point detection device includes,

[0085] The first detection module 201 is used to scale the image to be detected to the first image size and input it into the trained first neural network to obtain the first palm image probability of the image to be detected, and determine whether the first palm image probability is greater than the first probability threshold;

[0086] The second detection module 202 is configured to scale the image to be detected to a second image size and input it into a trained second neural network when the probability of the first palm image is greater than the first probability threshold, to obtain the The second palm image probability of the image to be detected, judging whether the second palm image probabil...

Embodiment 3

[0100] Figure 8 It is a schematic diagram of a terminal device provided in Embodiment 3 of the present application. Such as Figure 8 As shown, the terminal device 3 in this embodiment includes: a processor 30 , a memory 31 , and a computer program 32 stored in the memory 31 and operable on the processor 30 . When the processor 30 executes the computer program 32, it realizes the steps in the embodiment of the above-mentioned palm and its key point detection method, for example figure 1 Steps S101 to S103 are shown. Alternatively, when the processor 30 executes the computer program 32, it realizes the functions of the modules / units in the above-mentioned device embodiments, for example Figure 7 The functions of modules 201 to 203 are shown.

[0101] Exemplarily, the computer program 32 can be divided into one or more modules / units, and the one or more modules / units are stored in the memory 31 and executed by the processor 30 to complete this application. The one or mor...

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Abstract

A method for detect palm and its key points include scaling image to be detected to first image size and inputting trained first neural network to obtain first palm image probability of that image tobe detected; When the probability of the first palm image is greater than the first probability threshold, zooming the image to be detected to a second image size and inputting the trained second neural network to obtain the second palm image probability of the image to be detected, wherein the second image size is greater than the first image size; Outputting second palm key point prediction coordinates predicted by the second neural network when the second palm image probability is greater than the second probability threshold. The present application can solve the problems of low accuracy and slow detection speed of existing palm and key point detection methods.

Description

technical field [0001] The present application belongs to the technical field of biometric identification, and in particular relates to a palm and its key point detection method, device and terminal equipment. Background technique [0002] With the development of science and technology, various biometric technologies have been applied in people's lives, such as fingerprint check-in, palmprint recognition and voiceprint authentication. [0003] Among these biometric technologies, palmprint recognition and palm vein recognition are techniques for personal identity verification that use the line characteristics of the palm and the palm vein distribution map respectively. In the process of palmprint recognition and palm vein recognition, palm detection and palm key point detection are extremely important links. Through palm detection, it can be judged whether there is a palm in an image, which is the basis for subsequent palm recognition. Point detection can realize palm positi...

Claims

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Application Information

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IPC IPC(8): G06T7/136G06K9/00G06T3/40G06T7/90
CPCG06T3/40G06T7/136G06T7/90G06T2207/10024G06V40/1365
Inventor 陈书楷钱叶青
Owner 厦门熵基科技有限公司
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