  Offside detection in soccer has emerged as one of the most important
decisions with an average of 50 offside decisions every game. False detections
and rash calls adversely affect game conditions and in many cases drastically
change the outcome of the game. The human eye has finite precision and can only
discern a limited amount of detail in a given instance. Current offside
decisions are made manually by sideline referees and tend to remain
controversial in many games. This calls for automated offside detection
techniques in order to assist accurate refereeing. In this work, we have
explicitly used computer vision and image processing techniques like Hough
transform, color similarity (quantization), graph connected components, and
vanishing point ideas to identify the probable offside regions.
  Keywords: Hough transform, connected components, KLT tracking, color
similarity.
