Ear image recognition method amalgamating wavelet analysis and matrix feature

A wavelet analysis and image recognition technology, applied in the field of personal identification, can solve problems such as noise interference, low calculation speed, and inaccurate values ​​of wavelet moment invariants

Inactive Publication Date: 2008-09-17
CHONGQING UNIV
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AI Technical Summary

Problems solved by technology

[0010] The above calculation formula needs to use coordinate transformation when calculating the wavelet moment invariant to transform the digital image from the rectangular coordinate system to the polar coordinate system, which will increase the conversion error after the transformation, resulting in inaccurate value of the wavelet

Method used

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  • Ear image recognition method amalgamating wavelet analysis and matrix feature
  • Ear image recognition method amalgamating wavelet analysis and matrix feature
  • Ear image recognition method amalgamating wavelet analysis and matrix feature

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Embodiment

[0102] A) In this experiment, computer recognition experiments were performed on 600 gray-scale images of 50 types of human ear pictures without noise and 600 noise-added pictures, in which the 12 states of each human ear are as follows: Figure 4 shown.

[0103] B) Gaussian noise with a variance of 0.01 is added correspondingly to each state (overlapping the high-period noise with the image).

[0104] C) First use 10 types of pictures to train the system (calculate the weight of the moment invariant) to obtain the weight of the invariant moment component. Then each class uses 400 images as training samples and the remaining 800 images as testing samples.

[0105] D) In ​​the recognition process, the collected human ear image is first subjected to wavelet modulus maximum value denoising processing and edge extraction using the method of step 2 in the embodiment, and then the image after processing is used in step 3 (1) of the embodiment In the method, the value of wavelet mo...

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Abstract

The invention relates to an ear image recognition method combining wavelet analysis and moment features, which is characterized in that the method comprises following steps: (1) preprocessing collected ear images: using wavelet transform modulus maxima to denoise for the collected ear images, and extracting ear image edge to gain wavelet decomposition modulus maxima edge images in various scales; (2) extracting characteristic value of the ear images: making use of an improved wavelet moment invariants arithmetic to calculate the wavelet moment invariants used for extracting the characteristic value of the ear images; (3) recognizing the ear: processing weighting and classifying the characteristic value of the ear images gained in the step (2), and recognizing the ear. The invention processes to extract the characteristic value of the ear via wavelet modulus maxima and the improved wavelet moment invariants arithmetic, and not only has a high calculation accuracy and a fast calculation speed, but also can improve discrimination of the collected ear images in the environment of poor illumination, illumination change and noise jamming.

Description

technical field [0001] The invention relates to a personal identification technology of human biological characteristics, in particular to a human ear image recognition method which combines wavelet analysis and moment features. Background technique [0002] In recent years, biometrics has attracted more and more researchers' attention. It plays an important role in almost everything from authentication to gate entry security. However, most of the biometric technologies at this stage have strict requirements on their working environment, thus limiting their scope of application. Therefore, researchers are working hard to find new biometric technologies. Human ear recognition is one of the new recognition technologies, and there are very few studies on it at home and abroad. Human ear recognition technology has considerable theoretical research value and practical application prospect due to its unique physiological characteristics and observation angles. It involves many ...

Claims

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Application Information

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IPC IPC(8): G06K9/00
Inventor 刘嘉敏谢海军钱凤魏彪潘银松李以农刘强
Owner CHONGQING UNIV
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