3rd meeting of young researchers at UP 1 - IJUP - Universidade do ...

Automatic Shooting Sport Target Classification System
Rui Diogo Ribeiro Barbosa 1 , Leonardo Veríssimo Cardoso 2
1 Department of Electrical and Computer Engineering, Faculty of Engineering University of Porto,
Portugal.
2 Department of Electrical and Computer Engineering, Faculty of Engineering University of Porto,
Portugal.
Digital photography technology evolution enabled continuous decrease of price per megapixel.
So it became possible to use a common digital camera in systems that require precision image
processing, such as classifying official shooting sports targets. This project has been developed
as a low cost solution, for shooting sport target classification, and as an option to the use of
specific classifying machines that are actually used. The project was primarily focused on
developing software that automatically classifies the targets.
The photos used, to test the developed software, were taken in the laboratory, where a tripod
was used to hold the camera down and align it with the target. After configuring some
important parameters, like contrast and diaphragm aperture, the most important is to know the
minimum size in pixels needed to process the image because as the file size gets bigger the
more time the software takes to process.
The developed software can be divided into three parts:
i) Detection and calculation of the centers of the shots.
ii) Detection of the type of target and its center.
iii) Shot classification.
To detect shots on the targets, the photos were taken with a red sheet beyond them. This color
was chosen to detect the shots with a segmentation of the initial image. So the shots would be
red in the image.
Processing this image we get the edges of each shot. The centers are calculated using an
equation for centers of mass and then optimized by a least squares method.
Detecting the type of target and its center was based on images processed through the initial
photo and in an algorithm that detects the size of target’s black circle. Knowing that each target
has different width for its black circle, the center and the type of target are automatically
known.
Finally, through distance between points in a plane, and knowing that the radius of all shots is
the same, we get the distance between the center of the target and the closest point of the shot
to the center of the target, and, with that, the classification for each shot is made.
Graphic user interfaces, which gives an overview of the parameters used, and show the
obtained results, has been developed so the software can easily be used.
References:
[1] Avelino, Pedro (2006), Optical recognition of shots in a shooting sports target, FEUP
[2] The MathWorks, Inc. (1994-2010), Available at: http://www.mathworks.com
[3] International Shooting Sport Federation (2010), Available at: http://www.issf-sports.org
416 3 rd meeting of young researchers at UP