The application provides an image segmentation method and a system, and relates to the field of image processing. The method comprises the following steps: according to an original image, a first initial prospect area and an initial background area are delimited; down-sampling is carried out on the original image to obtain a first image, and pixels, which belong to the first initial prospect area, of the first image are delimited as an initial prospect area; pixels in the initial background area are utilized to establish an initial background mixed Gauss model, and the pixels in the initial prospect area are utilized to establish an initial prospect mixed Gauss model; the image is input into an image cutting process, and a new prospect area and a new background area are delimited; the pixels in the new prospect area are utilized to optimize parameters of the prospect mixed Gauss model, and pixels in the new background area are utilized to optimize parameters the background mixed Gauss model until that the image cutting process converges. According to the invention, a processing time of a cutting algorithm can be raised.

An image segmentation method and a system

The invention discloses a digital image processing based method for detecting the geometrical characteristics of an impurity in a polyolefin material The method comprises the following steps: S1, shooting a picture for a sample slice of the polyolefin material by using a microscope to obtain an original microscopic image of the sample slice; S2, dividing the original microscopic image obtained in the step 1 by using a marked watershed dividing method to obtain a possible impurity particle area; S3, determining a final impurity particle area according to the possible impurity particle area obtained in the step 2 according to the geometrical characteristics of the impurity; S4, marking the impurity particle area determined in the step 3 and counting the geometrical characteristic parameters of each impurity area According to the method, the existence of the impurity particles can be effectively identified, and the geometrical characteristics like size, number and area of the existing impurity particles can be accurately calculated

Digital image processing based method for detecting geometrical characteristics of impurity in polyolefin material

An image processing apparatus for extracting an area of a detection target from an image includes an image input section that acquires an image, an image generation section that generates a plurality of images with different resolutions from the image, and a segmentation section that performs segmentation using the plurality of images with the different resolutions. The segmentation section segments an image with a low resolution and then segmenting an image with a high resolution using, as a processing target area, an area in the image with the high resolution corresponding to an area near a boundary resulting from processing of the segmentation of the image with the low resolution.

Image processing apparatus and segmentation method

The invention relates to a color image cutting method based on spherical particle calculation The color image cutting method based on spherical particle calculation can effectively solve the problems that images cut in the prior art do not accord with visual effect of people and image cutting speed is low According to the technical scheme, the color image cutting method based on spherical particle calculation comprises the steps that firstly, RGB values of pixels of known color images are extracted; secondly, a spherical particle set is built according to the RGB values of the known color images; thirdly, spherical particles are merged; fourthly, a particle size threshold valve rhu is set, and a spherical particle template is built; fifthly, the RGB value of the pixel of a color image to be cut is extracted; sixthly, the RGB value of the pixel of the color image to be cut is expressed as a spherical particle; seventhly, the fuzzy inclusion degree between the atomic spherical particle of the color image to be cut and a spherical particle in the spherical particle template is calculated; eighthly, the RGB value of the pixel of the color image to be cut is determined; ninthly, the cut color image is saved The color image cutting method based on spherical particle calculation accelerates color image cutting, is good in cutting effect and is an innovation on color image cutting methods

Color image cutting method based on spherical particle calculation

The invention discloses a method for extracting region growing seed points based on remote sensing images and sea-land segmentation. The method includes: performing horizontal direction difference treatment on pixel values of pixel points of effective rows and obtaining a difference result; according to the difference result, selecting the effective row including the seed points from the effective rows; and determining the seed points in the effective row including the seed points. The seed points are automatically obtained by using scan image data and based on a pixel gradient method. The artificial interaction is avoided, and the algorithm efficiency is improved.

Method and system for extracting region growing seed points based on remote sensing images and sea-land segmentation

The invention relates to a quick and effective particle image segmentation algorithm which is derived from the classic waterline segmentation algorithm and simultaneously avoids the over-segmentation problem of the traditional waterline segmentation algorithm. The method comprises three parts of image pretreatment, segmentation algorithm and segmentation after-treatment, wherein the image pretreatment eliminates the influence of different noises by adopting a variable metric filter, the segmentation algorithm is introduced with the concept of marking arrays and marks the correspondence of all pixel points when the least value of gradient rises to the maximum value of the gradient, and the after-treatment compares the similarity level of adjacent areas by one-step scanning and merge the two areas if the similarity level of areas at two sides of a waterline is smaller than a set threshold value. The method can quickly and accurately segment a target particle from images and greatly enhances the computation speed.

Quick particle image segmentation method based on improved waterline algorithm

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Quick particle image segmentation method based on improved waterline algorithm