Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, ...

This project demonstrates how to perform image segmentation using the K-Means Clustering algorithm with Python, OpenCV, and Scikit-learn. The goal is to reduce the image complexity by grouping similar ...

Medical image segmentation has important auxiliary significance for clinical diagnosis and treatment. Most of existing medical image segmentation solutions adopt convolutional neural networks (CNNs).

In the past decade, people's interest in computer vision has grown. Stable multiplication rate boost with powerful computing power every 13 months, face detection and recognition has changed from ...

Deep learning has become an active research topic in the field of medical image analysis. In particular, for the automatic segmentation of stomatological images, great advances have been made in ...

One of the most popular methods for image segmentation is called the Watershed algorithm. It is often used when we are dealing with one of the most difficult operations in image processing – ...