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A palmar vein feature extraction method based on a multi-scale convolution kernel

A feature extraction and convolution kernel technology, applied in subcutaneous biometrics, biometric identification, instruments, etc., can solve the problems of not being suitable for extracting palm vein features, and the recognition effect is not obvious.

Active Publication Date: 2018-12-11
广州麦仑信息科技有限公司
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Problems solved by technology

If these network structures are directly applied to palm vein recognition, the recognition effect is not obvious, because the network structure is not suitable for extracting the palm vein features of the network structure.

Method used

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  • A palmar vein feature extraction method based on a multi-scale convolution kernel
  • A palmar vein feature extraction method based on a multi-scale convolution kernel
  • A palmar vein feature extraction method based on a multi-scale convolution kernel

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Embodiment Construction

[0023] In order to make the object of the present invention and the technical solution clearer, the present invention will be further described below in conjunction with the accompanying drawings.

[0024] Such as figure 1 As shown, a palm vein feature extraction method based on multi-scale convolution kernel, using a multi-scale convolution kernel feature extraction network, as follows:

[0025] (1) Input layer

[0026] The input layer data of the multi-scale convolution kernel feature extraction network is the preprocessed palm vein image, such as figure 2 As shown, picture a is the ROI region image of the palm vein collected by near-infrared light. After processing such as binarization and image enhancement, picture b is obtained. It is the palm vein image after preprocessing. It can be clearly seen that the palm vein image is special The network structure of the palm vein image is used as the input layer of the feature extraction network of the multi-scale convolution k...

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Abstract

The invention discloses a palmar vein feature extraction method based on a multi-scale convolution kernel. Aiming at the particularity of the palmar vein image texture, an irregular convolution kernelis used to detect the transverse and longitudinal network structure of palmar vein, and a multi-scale convolution kernel feature extraction network for palmar vein recognition is designed, which is mainly composed of four modules, namely a perceptual layer, a dimension reduction layer, a feature fusion layer and a feature vector representation layer. The technical scheme of the invention can makethe feature extraction network have good adaptability and effectiveness to the palmar vein feature extraction through the irregular convolution kernel, such as 3x7, 7x3, 1x7, 7x1, aiming at the characteristics of the palmar vein image such as a special network structure, easy deformation, weak local correlation, complex topological structure and the like.

Description

technical field [0001] The invention relates to the technical field of palm vein feature recognition, in particular to a palm vein feature extraction method based on a multi-scale convolution kernel. Background technique [0002] Palm vein recognition is an emerging biometric identification technology, which utilizes the hemoglobin in human palm blood to have strong absorption characteristics for near-infrared light, and obtains the distribution patterns of palm veins for identification. Palm vein recognition not only has the advantages of non-contact authentication and high reliability, but also requires live detection, which cannot be falsified and has a high level of security. With the development of technology, palm vein recognition technology is gradually applied to security systems, building access control, financial banks and other fields. [0003] In recent years, the methods of palm vein feature extraction and recognition can be roughly divided into two categories:...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V40/10G06V40/14G06N3/045G06F18/213G06F18/24
Inventor 余孟春谢清禄王显飞
Owner 广州麦仑信息科技有限公司
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