Image edge detection method

A detection method and image edge technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve the problems of poor anti-noise ability, low degree of automation, and affecting the accuracy of edge detection, so as to improve the degree of automation and avoid edge detection. Effects that blur, improve the ability to suppress spurious edges

Inactive Publication Date: 2011-08-17
SHANGHAI MARITIME UNIVERSITY
View PDF4 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the algorithm has the following three main disadvantages: (1) Canny operator only calculates the gradient amplitude by finding the mean value of finite difference in the 2×2 neighborhood. Although the edge location is accurate, the anti-noise ability is poor; (2) In the process of non-maximum value suppression, the Canny algorithm uses the gradient value of eight neighboring pixels to judge whether the current point has a local maximum value, which will affect the accuracy of edge detection; (3) the high and low thresholds of the Canny algorithm are both It is fixed, and the high and low thresholds are completely dependent on manual settings, so its degree of automation is low

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
  • Image edge detection method
  • Image edge detection method
  • Image edge detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0015] The purpose of the present invention is to address the deficiencies in the prior art, on the basis of analyzing and summarizing the Canny algorithm and the improved algorithms of the predecessors, to propose an image edge detection method, which is an improvement to the Canny edge detection method. First, the gradient of the image is calculated by using the 12-neighborhood method, and then the eigenvalue of the inverse difference moment is introduced to adaptively change the Gaussian space coefficient and the threshold, so that the method can accurately detect the edge of the image. The scheme of the present invention is:

[0016] 1. Improve the calculation method of gradient amplitude

[0017] The traditional Canny operator calculates the gradient magnitude by calculating the difference in the 2×2 neighborhood. This method is sensitive to noise. This paper proposes a method to calculate the x-direction and y-direction in 12 neighborhood pixels. The method of order par...

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 an image edge detection method in the field of image detection. The method comprises the following steps of: acquiring an image by using a camera and then calculating gradient amplitude and direction by using a method for calculating first-order partial derivative difference of x direction and y direction in 12 neighborhood pixels, thereby suppressing noise in the image and preventing edge blur of the image; then establishing a mapping relation between inverse difference moment characteristic values of a gray level co-occurrence matrix and Gaussian space factors as well as thresholds, adaptively varying the Gaussian space factors and high and low thresholds of edge detection to guarantee continuous extraction of image edge points; and finally detecting the image edge points according to a non-local maximum inhibition principle, thereby improving accuracy of image edge detection.

Description

Technical field: [0001] The invention relates to image edge detection in the field of automation, in particular to a method for image edge detection, which is suitable for image texture feature analysis, image segmentation, and graphic feature extraction in the field of computer vision. Background technique: [0002] In order to improve the performance of image edge detection, Canny proposed in 1986 that an excellent edge detection operator should meet the following three criteria (John CANNY. A computational approach to edge detection [J]. IEEE Trans Pattern Analysis and Machine Intelligence, 1986, 8 (6): 679~698): (1) Good signal-to-noise ratio, that is, the probability that a non-edge point is misjudged as an edge point or an edge point is misjudged as a non-edge point is low, so that the output signal-to-noise ratio reaches (2) Good positioning performance, that is, the detected image edge point should be in the center of the actual image edge as much as possible; (3) Un...

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 Applications(China)
IPC IPC(8): G06T7/60G06T5/00
Inventor 陈长风王建华黄萍萍熊亚洲张晓杰冯海涛
Owner SHANGHAI MARITIME UNIVERSITY
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