Abstract:  This paper proposes a soccer detection method that combines the attention selection model of phase spectrum of quaternion Fourier transform (PQFT) and pulse coupled neural network (PCNN). In the preprocessing, the region outside the field is removed, and the region of interest extracted using PQFT. The
target is detected according to the physical characteristics such as color, shape and size. If no candidate or more than one are detected, a Kalman filter is used to make prediction. Simulation shows that the identification rate is improved by 9.6% and 14.9% respectively as compared to the dynamic Kalman filtering with velocity control and the real time ball detection framework introduced in the literature.

Key words: soccer detection, quaternion Fourier transform, pulse coupled neural network, attention selection, Kalman filter