A metallographic image edge detection method based on mathematical morphology

A mathematical morphology and image edge technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problems of enhancing high-frequency components, long operation time, and large amount of calculation, to achieve accurate positioning, edge continuity and Smooth, targeted effect

Pending Publication Date: 2019-03-29
NANJING UNIV OF SCI & TECH
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Problems solved by technology

Commonly used traditional edge detection algorithms include: first-order differential edge detection operators include Robert gradient operator, Sobel operator, Prewitt operator, etc. These operators are sensitive to noise and have poor noise resistance. It will strengthen the noise, and the amount of calculation is relatively large
The operators of the second-order differential edge detection include Laplacian operator, Kirsh operator, Walks operator and other nonlinear operators. This kind of operator is similar to high-pass filter, which has the function of enhancing high-frequency components. Therefore, for noise More sensi

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  • A metallographic image edge detection method based on mathematical morphology
  • A metallographic image edge detection method based on mathematical morphology
  • A metallographic image edge detection method based on mathematical morphology

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[0052] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0053] combine Figure 1~2 , the present invention is based on the metallographic image edge detection method of mathematical morphology, comprises the following steps:

[0054] Step 1, metallographic image acquisition and preprocessing: convert the metallographic image into a contrast-balanced grayscale image, and filter and sharpen the grayscale image to reduce noise and enhance edge information;

[0055] Step 1.1, image acquisition: first collect the metallographic image through an optical microscope and a digital camera, and then input the metallographic image into the computer;

[0056] Step 1.2, image preprocessing: first convert the image into a color space, convert the color image into a single-channel gray image, and then use the mean filtering method to perform mean filtering and sharpening on the obtained metallographic grayscale im...

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Abstract

The invention discloses a metallographic image edge detection method based on mathematical morphology. Firstly, the metallographic image is converted into a contrast-equalized gray-scale image to reduce noise and enhance edge information. Then the histogram of the image is computed, the histogram is normalized, the integrals of the histogram are computed, and the integrals of the histogram are used as a look-up table for image transformation. Secondly, two thresholds of segmented images are generated by a self-defined improved algorithm based on iterative method. The foreground image and background image of the image are segmented by the two thresholds respectively. NAND operation is performed on the two images to remove the grains-independent structures from the images. Finally, the edgeimage of the grain is obtained by the self-defined multi-scale and multi-structure algorithm. The invention reduces the boundaries of missed detection, multiple detection and false detection, the extracted edges have better continuity and smoothness, and the positioning of the boundaries is more accurate, and the characteristics of the metallographic images are fully considered, so that the pertinence is stronger.

Description

technical field [0001] The invention belongs to the technical field of image processing or computer vision, in particular to a metallographic image edge detection method based on mathematical morphology. Background technique [0002] As a comprehensive subject, metallography research mainly includes the following three contents: Basic theoretical research: mainly involves the application of mathematical methods such as stereology principles, geometry, topology, probability theory and mathematical statistics; testing methods and equipment instruments Research: mainly includes image processing and testing technology calculation programs and error analysis, etc.; applied research: mainly includes all aspects of theoretical research in materials science and automatic inspection and control of material production processes. [0003] At present, in quantitative metallography, scholars at home and abroad have done a lot of research on metallographic image processing technology, and...

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Application Information

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IPC IPC(8): G06T7/12G06T7/136G06T7/194
CPCG06T7/12G06T7/136G06T7/194G06T2207/20024G06T2207/10024G06T2207/10004
Inventor 甄海洋李军钱世豪马佶辰邹奉天
Owner NANJING UNIV OF SCI & TECH
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