Basketball Recognition in Complex Backgrounds

Semantic object recognition is one of key issues in intelligent image understanding and so on. In this paper, we design algorithms to recognize basketballs in complex backgrounds. First, color feature is extracted to determine the possible regions of basketball. Then steerable filters are combined with modified hough transform to extract the circle contour, by which candidate basketballs are extracted. Finally, the candidate basketballs are confirmed using template matching by the texture image of basketballs. Experimental results con-firm the efficiency of algorithm. And the proposed algorithms can be user for recognition of other balls such as volleyballs, footballs and so on.