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Image processing clustering method and system and electronic device

A technology of image processing and clustering methods, applied in the field of image visual processing, can solve problems such as poor image clustering processing, and achieve the effect of ensuring accuracy

Inactive Publication Date: 2019-10-18
创新奇智(重庆)科技有限公司
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AI Technical Summary

Problems solved by technology

[0003] In order to solve the technical problem of poor processing of existing image clustering, the present invention provides an image processing clustering method and its system, and electronic equipment

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  • Image processing clustering method and system and electronic device
  • Image processing clustering method and system and electronic device
  • Image processing clustering method and system and electronic device

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Embodiment Construction

[0038] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0039] Provided in the present invention, the improved DBSCAN clustering algorithm (Density-Based Spatial Clustering of Applications with Noise) is a density-based clustering algorithm, which is different from existing partition and hierarchical clustering methods, which define clusters It is the largest set of density-connected points, can divide regions with sufficiently high density into clusters, and can find clusters of arbitrary shape in noisy spatial databases.

[0040] Several definitions in the DBSCAN clustering algorithm:

[0041] E Neighborhood: The area within the radi...

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Abstract

An image processing clustering method provided by the invention comprises the following steps: reducing the size of a mask image to obtain data to be clustered, and generating a first clustering dataset; performing DBSCAN clustering processing on the first clustering data set to obtain a cluster region, deleting semantic annotations in the first mask image based on the cluster region, and re-extracting data needing to be clustered of the first mask image; and combining the clustering results of the two parts to obtain a final clustering result. According to the method, rapid clustering of large-scale samples can be realized, and features of part of small-area features covered by large-range features can be re-extracted, so that the accuracy of a clustering result can be ensured. Comparedwith an existing clustering processing method, the problem that a small number of features in a small partial region range are omitted in the clustering processing process can be avoided. The invention further provides an image processing clustering system and an electronic device, and the image processing clustering system and the electronic device have the same beneficial effects as the method.

Description

【Technical field】 [0001] The invention relates to the field of image visual processing, in particular to an image processing clustering method, a system thereof, and an electronic device. 【Background technique】 [0002] In image processing, the methods involved include semantic segmentation technology, traditional image vision algorithms, etc. Among them, taking the semantic segmentation technology as an example, in the process of processing the semantic style of the image, each pixel is assigned a label, so that each pixel is classified, and then the labeled pixels can be clustered. However, the accuracy and processing time of existing clustering algorithms are often affected by many factors such as image size, pixel density, and parameter settings, which in turn have an important impact on the overall model. 【Content of invention】 [0003] In order to solve the technical problem of poor image clustering processing in the prior art, the present invention provides an imag...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/34G06T3/40G06T7/136
CPCG06T3/4007G06T7/136G06V10/267G06F18/23
Inventor 张发恩杨经宇袁智超
Owner 创新奇智(重庆)科技有限公司
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