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Image data clustering method and device

An image data and clustering method technology, applied in the field of image processing, can solve problems such as poor image data clustering effect, and achieve the effect of eliminating subjectivity and accurate clustering results.

Active Publication Date: 2020-09-04
HENAN NORMAL UNIV
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a method and device for clustering image data to solve the problem that the clustering effect of image data is not good at present

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  • Image data clustering method and device

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Embodiment Construction

[0046] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0047] method embodiment

[0048] Considering that the DPC algorithm and other clustering algorithms have poor clustering effect when clustering image data, the present invention provides a new image clustering method, which is based on the existing image clustering method using DPC In the above, two improvements are proposed: one is to use the weighted Euclidean distance and the degree of mutual adjacency to calculate the density of data points; the other is to use its own recommendation strategy to automatically determine the local center point, and then form a micro-cluster based on the determined local center point, and propose The strategy of merging micro-clusters and micro-clusters with less border points in its neighbor clusters to get the final clustering result. The implementation process is as follows figure 1 shown. The implem...

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Abstract

The invention relates to an image data clustering method and device, and belongs to the technical field of image processing. According to the method, firstly, a self-recommendation strategy is proposed to determine a local center point, the subjectivity of manually selecting a cluster center is eliminated, and the problem that the center point of a cluster with low density is ignored is solved; the local central point is taken as a micro-cluster central point to distribute residual data points, and further a plurality of micro-clusters are generated; and finally, a micro-cluster merging strategy is proposed, and the micro-clusters and the micro-clusters containing fewer boundary points in the adjacent clusters thereof are merged because the micro-clusters are closer to the cluster center and more likely to be located in the same cluster as the micro-clusters, so that the clustering result of the method is more accurate.

Description

technical field [0001] The invention relates to a clustering method and device for image data, belonging to the technical field of image processing. Background technique [0002] Cluster analysis is an unsupervised classification method. Its goal is to divide the data set without classification labels into several clusters, and at the same time ensure that the objects in the clusters are similar to each other and the objects in the clusters are not similar. It can be applied to optimization analysis, image segmentation, bioinformatics and many other fields. [0003] Clustering methods can be used to classify image data. The density peak clustering algorithm (Clustering byfast search and find of density peaks, DPC) is a clustering method proposed by Alex and Laio. To its application more and more widely. The proposal of DPC is based on two assumptions: (1) the cluster center is surrounded by neighbors with lower density than it; (2) the distance between the cluster centers ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/23
Inventor 孙林秦小营孙全党李文凤
Owner HENAN NORMAL UNIV
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