Adaptive Image Edge Extraction Based on Discrete Algorithm and Classical Canny Operator

Phusit Kanchanatripop,Dafang Zhang

doi:10.3390/sym12111749

Abstract

In order to improve the accuracy of image edge detection, this paper studies the adaptive image edge detection technology based on discrete algorithm and classical Canny operator. First, the traditional sub-pixel edge detection method is illustrated based on the related literature research. Then, Canny operator is used for detection, the edge model of the quadric curve is established using discrete data, and the adaptive image edge parameters are obtained using one-dimensional gray moment. Experimental results show that the accuracy of feature detection is 99%, which can be applied to the practice of image edge detection to a certain extent.

Highlights

Image edge extraction plays an important role in image recognition and processing
The above has introduced the sub-pixel image edge extraction technology based on the discrete algorithm and Canny operator in detail (See the Appendix A for specific programming), and we will use this algorithm to explain the specific process of image processing, as shown in the Figure 2
In order to improve the accuracy of adaptive image edge detection, this paper introduces the

Summary

Introduction

Image edge extraction plays an important role in image recognition and processing. In the manufacturing process of some high precision devices, the accurate registration and recognition of parts have put forward higher precision requirements for the image edge detection and extraction technology [3]. Due to the high cost of updating the system, this paper chose to improve the image edge detection and extraction technology and studied adaptive image edge extraction technology based on the discrete algorithm and the classical Canny operator. Adaptive image edge extraction technology based on the discrete algorithm and the classical Canny operator is studied. The Canny edge detection operator and sub-pixel edge detection method are introduced, and a quadratic curve edge model based on discrete data is proposed. The simulation test and the analysis of the good result for edge detection method are carried out to prove its feasibility

Related Work

Design and and Analysis

Accuracy

Findings

Conclusions