Machine learning on edge detection

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 algorithm...

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Bibliographic Details
Main Author: Yu, Lu
Other Authors: Qian Kemao
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166100
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Institution: Nanyang Technological University
Language: English
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Summary: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.