Method for segmenting textile and medicine images

An image segmentation and image technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of noise sensitivity, over-segmentation, etc., and achieve the effect of improving accuracy, reliable technical means, and improving over-segmentation phenomenon

Inactive Publication Date: 2012-07-04
JIANGNAN UNIV
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Problems solved by technology

[0004] In order to overcome the shortcomings of existing watershed algorithms that are sensitive to noise and prone to over-segmentation, the present invention proposes an image segmentation method that can improve over-segmentation

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  • Method for segmenting textile and medicine images
  • Method for segmenting textile and medicine images
  • Method for segmenting textile and medicine images

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Embodiment Construction

[0007] The first step is to use the one-dimensional gradient vector flow partial differential equation to perform boundary information diffusion and noise removal on the gradient amplitude image. Specifically, the original gradient vector flow GVF used for diffusing two-dimensional gradient vectors is modified into a partial differential equation for diffusing one-dimensional gradient amplitudes, namely 1D-GVF:

[0008] μ ▿ 2 g - f 2 ( g - f ) = 0 - - - ( 1 )

[0009] Among them, f represents the gradient magnitude image of the original image, μ is the weight factor, Is the gradient operator, g is the diffusion effect of partial differential equation on f, and its initial value is f. The minimizing energy functional corresponding to formula (1) is:

[0010] ϵ = ∫ ∫ μ | ▿ g | 2 + f 2 ( g - f ) 2 dxdy - - - ( 2 )

[0011] Through the function of 1D-GVF, the boundary ...

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Abstract

The invention discloses a method for segmenting textile and medicine images, which improves the over-segmentation in an image watershed algorithm and comprises the following steps of: firstly, carrying out boundary detection on an original image for obtaining a gradient amplitude image; secondly, carrying out boundary information diffusion and noise removal on the gradient amplitude image by using a one-dimensional gradient vector flow partial differential equation; thirdly, detecting local minimum value points of the gradient image, and automatically merging similar local minimum value points through morphology dilatation operation; and finally, segmenting the processed image by using the watershed algorithm.

Description

Technical field [0001] The invention relates to an image segmentation method, in particular to an image segmentation method capable of improving over-segmentation phenomenon. Background technique [0002] Image segmentation is a key task in the field of computer vision. Among various segmentation algorithms, watershed is a better algorithm. It takes gradient amplitude image as the processing object, can automatically segment each target object in the image, and is widely used in image processing. Analyzed in principle, the watershed is a region-based image segmentation method. [0003] At present, a recognized serious shortcoming of the watershed algorithm is that it is sensitive to noise and prone to over-segmentation, that is, the number of segmented regions far exceeds the actual number of objects contained in the image. The reason is that each actual object area often contains multiple local minima. According to the principle of segmentation, each local minimum will produce...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 周頔吉庆
Owner JIANGNAN UNIV
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