Image partition method based on neighbor-hood PCA (Principal Component Analysis)-Laplace

A technology of principal component analysis and image segmentation, which is applied in the field of image processing and can solve problems such as noise sensitivity

Active Publication Date: 2015-05-20
光宇锦业(武汉)智能科技有限公司
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide an image segmentation method based on Neighborhood Principal Component Analysis-Laplace for the defects in the prior art. This method solves the problem of edge extraction in the existing similar segmentation

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[0045] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the 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.

[0046] The present invention implements the image segmentation method based on neighborhood principal component analysis-Laplacian to carry out principal component analysis to the original image to extract the main components of the image; then, use the Laplacian operator to perform edge detection on the image, thereby realizing the Image segmentation. figure 1 The main two images in , the left is the input image, and the black arrow points to the algorithm part. The lower right corner is the output image, which is pointed to by a thin arrow after being processed by the method in this paper. exist figure 1 The part frame...

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Abstract

The invention discloses an image partition method based on neighbor-hood PCA (Principal Component Analysis)-Laplace. The method comprises the steps of carrying out PCT on an original image to obtain a feature vector of each pixel; extracting the main ingredients of an image to effectively restrain noise; carrying out edge detection on the image by a Laplace operator so as to realize image segmentation. Compared with a traditional Sobel operator partitioning algorithm and an LOG operator partitioning algorithm, the method is used for carrying out the PCA on the image pixels to estimate parameter values in a de-noising process in a way of being independent of an empirical value, so as to effectively reduce the interference on the image by the noise, and simplify the computation complexity. Experimental results show that the method can improve the segmentation effect of the image and is strongly excellent in accuracy and robustness.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image segmentation method based on neighborhood principal component analysis-Laplace. Background technique [0002] Image segmentation technology has penetrated into all aspects of life. For example, in biological and medical image analysis, cells, tissues and organs need to be separated from the image to measure their shape and cross-sectional images, so as to perform quantitative and qualitative analysis and evaluation of diseased tissues. and forecast. With the development of visual information capture equipment and technologies such as video cameras, cameras, infrared rays, and various sensors, the acquisition of visual information has become a simple problem, but how to obtain the interesting part from a large number of visual information has become an important research direction. Especially when the acquired image contains noise, how to obtain more accurate de...

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Application Information

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IPC IPC(8): G06T7/00G06T5/00
CPCG06T5/002
Inventor 卢涛万永静张彦铎李晓林杨威余军鲁统伟闵锋周华兵朱锐李迅魏运运黄爽段艳会张玉敏
Owner 光宇锦业(武汉)智能科技有限公司
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