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Feature extracting method, device and pattern recognition method and device

A feature extraction and recognition technology, applied in the field of image processing, can solve problems such as poor stability and achieve high stability

Active Publication Date: 2008-04-09
北京中星天视科技有限公司
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Problems solved by technology

[0019] It can be seen from the above technical solutions that when using the 2DLDA method for feature extraction, step 103 and step 106 respectively include matrix inversion operations. Since not all matrices have inverse matrices, therefore, using the 2DLDA method for feature extraction Poor stability

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  • Feature extracting method, device and pattern recognition method and device
  • Feature extracting method, device and pattern recognition method and device
  • Feature extracting method, device and pattern recognition method and device

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Embodiment Construction

[0032] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the drawings and preferred embodiments.

[0033] FIG. 2 is a flowchart of a feature extraction method provided by an embodiment of the present invention.

[0034] Suppose there are c samples, the total number is N, each sample has D original features, and each sample can be uniquely represented by a two-dimensional matrix, and the number of samples of the i class is N i , the j-th sample in the i-th class is I j (i) , the mean of the samples of class i is The mean of all samples is in I ‾ ( i ) = 1 N i Σ j = ...

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Abstract

The invention discloses a feature extraction method. The method includes steps: acquiring a unidirectional projection matrix formed by a first determined number of eigenvectors corresponding to the maximum eigenvalues of the difference matrix of a first inter-class scatter matrix and a first intra-class scatter matrix of a sample matrix including more than one class of samples, and projecting the sample matrix onto the unidirectional projection matrix to obtain a unidirectional characteristic sample matrix; and acquiring a bidirectional projection matrix formed by a second determined number of eigenvectors corresponding to the maximum eigenvalues of the difference matrix of a second inter-class scatter matrix and a second intra-class scatter matrix of the transposed matrix of the unidirectional characteristic sample matrix, and projecting the transposed matrix of the unidirectional characteristic matrix to the bidirectional projection matrix to obtain bidirectional characteristic samples. The invention also discloses a feature extraction device and a pattern recognition method and a device. Applying the inventive method and the device can improve stability and speed for feature extraction and pattern recognition.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a feature extraction method and device, and a pattern recognition method and device. Background technique [0002] Feature extraction is an important step in pattern recognition, and the feature extraction device is an important part of the pattern recognition system. Feature extraction methods and devices are widely used in image processing fields such as face detection and face recognition. The core idea of ​​feature extraction is: compress the D original feature quantities of the sample into d feature quantities, so that the sample with D original feature quantities can be represented by the feature samples with the d feature quantities, and the d is less than d. According to mathematical principles such as matrix theory, the above-mentioned feature extraction can be realized, and the mathematical transformation process for feature extraction can be as follows: Assume that th...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/00
Inventor 王磊
Owner 北京中星天视科技有限公司
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