An Image Segmentation Based on a Piecewise Smooth Model in Deep Learning

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초록

We propose simple method that can solve the image segmentation problem in unsupervised manner. Our convolutional neural network is based on ResNet-18 to construct auto-encoder structure since the results with the ResNet-18 are reasonable. Our network optimizes the traditional segmentation algorithms: Chan-Vese algorithm and Mumford-Shah algorithm. Compared to some unsupervised segmentation algorithms that need additional modules to cover the inaccurate boundaries, our method can be trained end-to-end and consists of a simple objective function. © 2022 IEEE.

키워드

Chan-Vese algorithm; image segmentation; Mumford-shah algorithm; unsupervised learning
제목
An Image Segmentation Based on a Piecewise Smooth Model in Deep Learning
저자
Choi, H.-T.; Derbel, B.; Hong, Byung-Woo
DOI
10.1109/ITC-CSCC55581.2022.9894902
발행일
2022-07
유형
Proceedings Paper
저널명
ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications
페이지
294 ~ 297