Deep Learning for Crack-Like Object Detection

Kaige Zhang, Heng-Da Cheng

• Publisher: CRC Press
• Year: 2023
• Print ISBN: 9781032181189
• eBook ISBN: 9781000871319
• Topic: Computer Science
• Subtopic: Computer Engineering
• Index: Computer Science

Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems.

This book discusses crack-like object detection problem comprehensively. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. It provides a detailed review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.

Table of contents

• Cover Page
• Title Page
• Copyright Page
• Preface
• Contents
• 1 Introduction
• 2 Crack Detection with Deep Classification Network
• 3 Crack Detection with Fully Convolutional Network
• 4 Crack Detection with Generative Adversarial Learning
• 5 Self-Supervised Structure Learning for Crack Detection
• 6 Deep Edge Computing
• 7 Conclusion and Discussion
• References
• Index