A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Regional Active Contours based on Variational level sets and Machine Learning for Image Segmentation
[article]
2015
arXiv
pre-print
Image segmentation is the problem of partitioning an image into different subsets, where each subset may have a different characterization in terms of color, intensity, texture, and/or other features. Segmentation is a fundamental component of image processing, and plays a significant role in computer vision, object recognition, and object tracking. Active Contour Models (ACMs) constitute a powerful energy-based minimization framework for image segmentation, which relies on the concept of
arXiv:1511.00111v1
fatcat:lba7gzjkivdn5a5hueow33t3bi