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A new information fusion approach for image segmentation - IEEE Xplore
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In this paper we propose a new hybrid image segmentation algorithm that integrate the region-based method with the boundary-based method.
In this paper we propose a new hybrid image segmentation algorithm that integrate the region-based method with the boundary-based method.
segmentation algorithm that integrate the region-based method with the boundary-based method. More specifically we take an information fusion approach based ...
People also ask
What is the approach of image segmentation?
Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics. Model of a segmented left human femur.
Which model is best for image segmentation?
Panoptic Segmentation
This mode of image segmentation provides the maximum amount of high-quality granular information from machine learning algorithms. It is useful in applications where the computer vision model needs to detect and interact with different objects in its environment, like an autonomous robot.
What are the three types of image segmentation?
Broadly speaking, image segmentation is used for three types of tasks: semantic segmentation, instance segmentation and panoptic segmentation. The difference between each type of image segmentation task lies in how they treat semantic classes: the specific categories a given pixel might be determined to belong to.
Which algorithm is best for image segmentation?
Algorithm | Description | Advantages |
Mask R-CNN | Gives three outputs for each object in the image: its class, bounding box coordinates, and object mask | a. Simple, flexible and general approach b. It is also the current state-of-the-art for image segmentation |
Oct 16, 2024 · The fused representations are capable of supporting a variety of downstream tasks, including image fusion, image segmentation, and object ...
We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps.
This paper proposes a new and reliable segmentation approach based on a fusion framework for combining multiple region-based segmentation maps.
Sep 17, 2024 · We introduce a novel image-level fusion based multi-modality medical image segmentation method, Fuse4Seg, which is a bi-level learning framework.
Jun 3, 2024 · Our research introduces an innovative Joint Spatial-Spectral Information Fusion method that requires no additional data collection.
Oct 10, 2020 · Considering non-optimal weather conditions, Pfeuffer and Diet- mayer [56] investigated a robust fusion approach for foggy scene segmentation.
Jun 19, 2019 · This work presents supervised classification algorithms based on information fusion for textured-images segmentation.