Football Sphericity Test using Computer Vision

Project Title

Project Area of Specialization

Artificial Intelligence

Project Summary

The sphericity testing of indoor soccer balls of circumference ranging from 68-70 cm set by the FIFA standards requires CSM Machine. The CSM (Circumference Sphericity Measurement) machine used for performing sphericity test of FIFA Footballs takes about 1 hour to test a single football sample. Using Artificial Intelligence with Machine Vision approach to perform the test would reduce the testing time and design expenditure. The implementation of Hough Transform and Convolutional Neural Network methods would be utilized to enable the system to record radius readings for sphericity calculation using high resolution camera instead of traditional sensor being used in CSM Machine. This would result in significance reduction of cost involved in developing the mechanical design and procuring the traditional sensor for replication of already available machine (CSM Machine). The testing time for a single football sample would be reduced to approximately 2 minutes. The machine can be controlled with a Windows compatible software providing the graphical analysis of the readings as well.

Project Objectives

The objectives of the project include; reduction of testing time for a single soccer ball in the industry and develop a cost effective model as compared to the traditional CSM Machine.

Project Implementation Method

The sphericity of the football would be calculated by recording video of the whole soccer ball specimen and then apply AI techniques i.e Hough Transform and CNN on every video frame to detect the flaws in sphericity or roundness.

Benefits of the Project

This project would benefit the industry to perform cost effective sphericity test in accordance with the FIFA standards and achieve results in less time.