Abstract
Background: Image segmentation is a very important problem in the field of image processing, complete and accurate image segmentation technology in many fields have extremely important applications, as described in various patents, but current segmentation methods in different applications exist great defects.
Method: This paper makes a detailed analysis of the development trend of image segmentation technology. And the methods based on the boundary segmentation, threshold segmentation, region growing segmentation, random field segmentation, neural network and wavelet calculation are introduced in detail, and the application direction and existing problems are summarized. Results: It can be seen that the image segmentation algorithm based on wavelet transformation has a better segmentation effect, Reasonable division of different types of images. Conclusion: Experiments have proved the application property of different methods, providing theoretical guidance for the design of a real-time, robust algorithm.Keywords: Image segmentation, image processing, boundary segmentation, neural network, wavelet calculation.
Related Books
Challenges and Opportunities for Deep Learning Applications in Industry 4.0
Recent Advances in IoT and Blockchain Technology
Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining
Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments Part II
Machine Learning and Its Application: A Quick Guide for Beginners
Computational Intelligence For Data Analysis
Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
Advanced Computing Techniques: Implementation, Informatics and Emerging Technologies
How to Design Optimization Algorithms by Applying Natural Behavioral Patterns
Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments (Part I)
10
1
1