Machine learning on edge detection

• Main Author: Yu, Lu
• Other Authors: Qian Kemao
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/166100
• Institution: Nanyang Technological University

Edge detection is a fundamental aspect of image processing and computer vision. It is used to detect and extract the borders of objects or regions from an image. Edge detection has been the subject of substantial research in the fields of image processing and computer vision, with numerous algorithms being developed over time. It has become an essential research area in the realm of edge computing. Recently, machine learning has emerged as a potent method for edge identification. Methods based on machine learning can be taught on a huge dataset of labelled images, enabling them to learn the edge properties from the data. This can allow for the development of extremely precise and robust edge recognition systems that can handle a wide variety of image kinds and changes, including some special edges. The purpose of this research is to analyse the efficacy of several machine learning approaches on edge detection.