Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.
The game of cricket and the use of technology
in the sport have grown rapidly over the past decade.
However, technology-based systems introduced to
adjudicate decisions such as run outs, stumpings,
boundary infringements and close catches are still
prone to human error, and thus their acceptance has
not been fully embraced by cricketing administrators.
In particular, technology is not employed for bat-pad
decisions. Although the snickometer may assist in
adjudicating such decisions it depends heavily on
human interpretation. The aim of this study is to
investigate the use of Wavelets in developing an edgedetection
adjudication system for the game of cricket.
Artificial Intelligence (AI) tools, namely Neural
Networks, will be employed to automate this edge
detection process. Live audio samples of ball-on-bat and
ball-on-pad events from a cricket match will be
recorded. DSP analysis, feature extraction and neural
network classification will then be employed on these
samples. Results will show the ability of the neural
network to differentiate between these key events. This
is crucial to developing a fully automated edge detection
system.
