Exploration of image and 3D data segmentation methods: an exhaustive survey
Hasnae Briouya, Asmae Briouya, Ali Choukri
Abstract
The field of image and 3-dimensional (3D) data segmentation is growing fast and has many uses, like in medicine, and robotics. In this article, we explain how computers understand and divide images and 3D data. We compare different ways of doing this in 2D and 3D, and look at the computer methods used. We also discuss recent work and what they discovered. This article gives a broad overview of what’s happening in this area of computer science. It explains the goals of the research, how they do it, and what they’ve found out. It’s a useful guide for researchers to understand what’s happening now and what challenges they might face in the future.
Keywords
2D data; 3D data; convolutional neural network; image; segmantation semantic;
DOI:
http://doi.org/10.12928/telkomnika.v22i2.25740
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