Project written as part of the "Geometric algorithms" course at AGH University of Science and Technology.

The leading programming language during this course: Python.

Convex hull is a fundamental concept in computational geometry. It refers to the smallest convex polygon that contains a given set of points in a plane or higher-dimensional space. Convex hulls have various applications in computer science and other fields. For instance, convex hulls are extensively used in computer graphics, image processing, and computational geometry for tasks such as collision detection, shape analysis and rendering. By computing the convex hull of a shape, one can extract important features and simplify the representation of complex objects. In GIS (Geographic Information Systems) applications, convex hulls are used to determine the boundary of a set of geographic points. In robotics, convex hulls are utilized for path planning algorithms. This can also be useful for defining region and analyzing data within a specific area.

The aim of the project was to familiarize oneself with various Convex Hull search algorithms, attempt their implementation and compare their actual runtime with their theoretical time complexity. Additionally, the project presented visualizations of the algorithms' operations, which can facilitate understanding of individual steps.