Image segmentation is the process of dividing an image into multiple segments or regions, each of which corresponds to a different object or part of the image.This is an important task in computer vision and image processing, as it enables the extraction of relevant information from images for further analysis and manipulation.
Image segmentation has various applications, including object detection and recognition, image editing, medical imaging, and video analysis. In video analysis, image segmentation can be used to track objects over time and analyze their motion and behavior.
Our project aims at trying to use Graph Cut alogorithm to solve this problem, and we also use K-means method, GMM(Gaussian Mixture Model) to handle this problem. Then comparing the results generated by different algorithms and analyse them.
Please run min_cut_8neighbor.m. The program automatically reads the saved image data and runs to get a graph variable. If you want to change the graph used for analysis, remove the read img.mat section and modify the imread section.
Next, run the FordFulkerson.m function to get the cut using the Ford Fulkerson method. It takes a long time to run.
If you encounter any issues or need further assistance, please:
Check the GitHub Issues page to see if someone has already reported the problem or if there is a solution available. If your issue is not listed, create a new issue, providing a detailed description of the problem, steps to reproduce it, and any error messages or screenshots that might be helpful. You can also contact the project maintainers via email or other communication channels provided in the repository for further assistance.
Shu Yang conlany@bu.edu
Zhenghao Sun szh1007@bu.edu
Xingyu Chen chxy517@bu.edu
Xingjian Zhang zhangzxj@bu.edu