A Laplacian edge detection method based on image interpolation

A technology of Laplacian operator and interpolation operation, applied in image analysis, image data processing, calculation, etc., can solve the problems of losing edge direction information, aggravating noise and adversely affecting edge detection results, etc.

Active Publication Date: 2021-05-21
ZHEJIANG IND & TRADE VACATIONAL COLLEGE
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] This template has the advantages of rotation invariance and displacement invariance, but it also has certain defects, such as the edge direction information may be lost during the edge detection process, and the adverse effect of noise on the edge detection results may also be aggravated.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Laplacian edge detection method based on image interpolation
  • A Laplacian edge detection method based on image interpolation
  • A Laplacian edge detection method based on image interpolation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] The present invention will be further described below in combination with specific embodiments. refer to Figure 1 to Figure 5 , The invention provides a Laplacian edge detection method based on image interpolation operation.

[0029] The Laplacian operator is a second-order derivative operator, which is a type of edge detection operator defined based on the second-order partial derivative in the direction of the two coordinate axes of the image. The second-order partial derivative of digital image element g(x, y) in the direction of x-axis and y-axis is defined as:

[0030]

[0031] The edge part of the image is often the part with large grayscale changes and jumps, so the first-order partial derivative corresponding to the edge part is often a local extremum, so the edge area of ​​​​the image corresponds to the corresponding position when the second-order partial derivative crosses zero. Therefore, the edge of the image can be detected through the zero-crossing p...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention provides a Laplacian edge detection method based on image interpolation operation, comprising the following steps, step 1: input the original image H, insert the average value between two adjacent pixel values ​​in each row of the original image value, and then insert the average value between two adjacent pixel values ​​in each column on the image after row interpolation to obtain the extended image H' after interpolation; Step 2: For 3*3 Laplacian template L Expand to obtain 5*5 Laplacian template L'; step 3: Convolve with 5*5 Laplacian template L' and extended image H' to obtain result image H". Beneficial effects achieved by the present invention It reduces the impact of noise on edge detection by interpolating the original image, and improves the edge detection effect by extending the Laplacian template.

Description

technical field [0001] The invention relates to an image edge detection method, in particular to an image interpolation-based Laplacian edge detection method. Background technique [0002] Digital images contain rich visual information, especially edge information in images, such as edge information of rivers in images, edge information of human bones in medical CT images, edge information of various zebra crossings in road traffic images, etc. The extraction of edge information is widely used in modern life, such as medical aided diagnosis, face recognition, target tracking, remote sensing monitoring and other fields. These edge information are very important for the recognition and detection of targets in images. The second order partial derivative of digital image element g(x, y) in the direction of x-axis and y-axis is defined as: The Laplacian edge detection operator is an edge detection operator based on the zero-crossing point of the second derivative on the edge, a...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/13
CPCG06T7/13
Inventor 杨鹏
Owner ZHEJIANG IND & TRADE VACATIONAL COLLEGE
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap