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Image clustering method and system

An image clustering and image technology, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of not fully retaining data characteristics, poor effect and projection direction, etc., to improve clustering accuracy and clustering efficiency , to avoid the effect of feature redundancy

Active Publication Date: 2021-08-24
广东云曌医疗科技有限公司
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Problems solved by technology

The commonly used principal component analysis (PCA) method does not fully preserve the structure of the data features; the trace ratio method (Trace Ratio) can make full use of the label information of the training set, but in actual use, it may get poor projection directions

Method used

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  • Image clustering method and system
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no. 2 example

[0061] Specifically, the second embodiment includes the following steps:

[0062] S210: Obtain an image data set according to the image to be processed;

[0063] Convert an image containing high-dimensional data into the following image data set X: X=[x 1 ,x 2 ,...,x n ]∈R d×n , where n is the number of samples and d is the feature dimension.

[0064] S220: Calculate the intra-class scatter matrix and the between-class scatter matrix of the image data set;

[0065] Solve the intra-class scatter matrix S according to the data set X w and between-class scatter matrix S b .

[0066] S230: Obtain a first projection matrix according to the gradient ratio and the objective function of the method;

[0067] Initialize the target projection matrix W first, and then solve the first projection matrix W according to the gradient ratio and the objective function of the method 1 * .

[0068] S240: Obtain a second projection matrix by using a gradient descent method according to t...

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Abstract

The invention discloses an image clustering method and system, and the method comprises the following steps: obtaining an image data set according to a to-be-processed image; processing the image data set to obtain a target projection matrix, wherein the sum of all projection directions of the target projection matrix is accumulated as an extreme value; performing dimension reduction on the image data set according to the target projection matrix to obtain an image subspace; and clustering the image subspace to obtain clustering information of the to-be-processed image. Dimension reduction processing before image clustering is achieved by finding the target projection matrix with the sum of all the projection directions accumulated as the extreme value, the structure of data features is reserved, it can be ensured that an optimal solution is found in each projection direction, the globally optimal projection direction is obtained. The problem of feature redundancy of image high-dimensional big data is avoided, and the clustering precision and the clustering efficiency are improved.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to an image clustering method and system. Background technique [0002] In recent years, with the development and popularization of the Internet, the amount of data such as images, videos, and texts and the feature vectors representing the data are increasing, that is to say, the dimensionality of the data is increasing. In order to utilize these massive data, it is necessary to cluster these high-dimensional data quickly and effectively. [0003] However, these high-dimensional big data contain a lot of redundant information, and the direct clustering effect is not good. Therefore, dimensionality reduction is used before clustering to reduce the data dimension and improve the effective utilization of data features. The commonly used principal component analysis (PCA) method does not fully preserve the structure of the data features; the trace ratio method (Trace Ratio) can make fu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/23213G06F18/2135
Inventor 杨晓君周科艺
Owner 广东云曌医疗科技有限公司
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