Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Morphological image edge detecting method based on quantum theory

A technology of quantum theory and detection methods, applied in image analysis, image data processing, instruments, etc., can solve problems such as thick edges, poor edge quality, discontinuity, etc.

Inactive Publication Date: 2015-07-15
DALIAN UNIV OF TECH
View PDF3 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method can roughly detect the edge of the image directly from the image disturbed by noise, but the detected edge is thick and there are discontinuities
When the noise increases, the possibility that some normal pixels are misjudged as noise by the measurement operator based on the mean square error increases, and the quality of the detected edge becomes worse and worse.

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
  • Morphological image edge detecting method based on quantum theory
  • Morphological image edge detecting method based on quantum theory
  • Morphological image edge detecting method based on quantum theory

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0050] In order to make the technical solutions and advantages of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the drawings in the embodiments of the present invention:

[0051] Such as figure 1 The shown morphological image edge detection method based on quantum theory comprises the following steps:

[0052] S1: Morphological edge detection based on quantum theory:

[0053] S11: Normalize the grayscale image f(x,y) to the interval [0,1], determine a central pixel, and define a superposition state structure element matrix SE according to the neighborhood grayscale information of the pixel with a size of n g (x,y);

[0054] S12: Construct a matrix g according to the gray level information of the central pixel neighborhood, measure the random number of the matrix g, after the measurement, the element value of the matrix g is 0 or 1, and the elements of the ma...

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 invention discloses a morphological image edge detecting method based on the quantum theory. The method comprises the following steps that S1, morphological edge detection is carried out based on the quantum theory; S2, edge thinning is carried out on an image in the mode of combining an NMS thinning algorithm and morphological thinning; S3, edge connection is carried out on the image through a quantum probabilistic method. When a quantum morphological edge detecting algorithm provided in the scheme is used for carrying out edge detection on a noise image, even though the strength of noise is large, the edge can be effectively extracted. Edge continuity can be effectively improved through an edge connecting algorithm based on quantum probability in the scheme.

Description

technical field [0001] The invention relates to the technical field of graphic edge processing, in particular to a quantum theory-based morphological image edge detection method. Background technique [0002] Edge detection is a basic image processing method, which has been widely used in image segmentation, image recognition and image analysis and other fields. Generally, in the process of image acquisition, transmission and processing, there will always be various noises inevitably, and the noise is mixed with the frequency bands at the edge of the image, which makes image edge detection difficult. Therefore, how to effectively obtain the image edge from the image disturbed by noise is an important research topic in image processing. [0003] Traditional edge detection methods based on Sobel, Roberts, Prewitt and other gradient operators and Laplacian operators are very sensitive to noise, and it is difficult to effectively detect the edge of noisy images. The Canny oper...

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
IPC IPC(8): G06T7/00
Inventor 陈喆殷福亮李润顺
Owner DALIAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com