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A Digital Image Processing Method Based on Clustering Algorithm of Selecting Appropriate Number of Clusters

A digital image and clustering algorithm technology, applied in image data processing, image analysis, calculation, etc.

Active Publication Date: 2019-05-21
SHANDONG EVAYINFO TECH CO LTD
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Problems solved by technology

[0007] The present invention introduces an optimization criterion to solve the influence of the number of clusters on the final segmented image

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  • A Digital Image Processing Method Based on Clustering Algorithm of Selecting Appropriate Number of Clusters
  • A Digital Image Processing Method Based on Clustering Algorithm of Selecting Appropriate Number of Clusters
  • A Digital Image Processing Method Based on Clustering Algorithm of Selecting Appropriate Number of Clusters

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Embodiment Construction

[0008] Terminology Explanation

[0009] 1. Quantiles, quantiles are quantile points, take quartiles as an example, that is, in statistics, arrange all values ​​​​from small to large and divide them into four equal parts. The values ​​at the three division points are quartile. In the present invention, the clustering number K is set, that is, all the pixels of the image to be segmented are arranged from small to large and divided into K equal parts, and the central value of each equal part is obtained as the initial cluster center.

[0010] 2. K-means clustering, an algorithm for finding data clusters in a data set, minimizes the cost function (objective function) of the difference measure.

[0011] Technical scheme of the present invention is as follows:

[0012] A digital image processing method based on a clustering algorithm for selecting an appropriate number of clusters, the specific steps comprising:

[0013] (1) Input grayscale image;

[0014] (2) Set the number of ...

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Abstract

The invention relates to a digital image processing method based on a clustering algorithm for selecting an appropriate number of clusters. The specific steps include: (1) inputting a grayscale image; (2) setting the number of iterative clustering numbers K; (3) searching Initial clustering center: use the concept of quantile to find the initial clustering center; (4) segment the image according to the standard k-means clustering step, and output the segmented image; (5) use the optimization criterion to select the optimal segmentation result. The present invention proposes an optimization criterion that can determine the number of clusters in a segmented image. It adopts the concept of intra-class difference and inter-class difference to obtain the best segmentation results with a small number of clusters. The invention has sufficient efficiency and stability, and has more advantages in running time than the traditional k-means algorithm.

Description

technical field [0001] The invention relates to a digital image processing method based on a clustering algorithm for selecting an appropriate number of clusters, and belongs to the technical field of clustering algorithm segmentation. Background technique [0002] In the field of image processing, image segmentation is very important for image classification and processing. Therefore, we need to divide these images into different regions and extract objects of interest. Among different image segmentation techniques, clustering is one of the important methods, and it is widely used in image segmentation of grayscale images. There are currently many clustering algorithms: k-means clustering; Fuzzy c-means clustering; mountain clustering and ISODATA methods, etc. One of the most commonly used algorithms is the k-means clustering algorithm. K-means algorithm is an unsupervised clustering algorithm, which has the characteristics of intuition, speed and easy implementation. A...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06K9/62
CPCG06F18/23213
Inventor 董祥军裴佳伦陈维洋
Owner SHANDONG EVAYINFO TECH CO LTD
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