Parallelization of irregular algorithms for shape detection

There are a series of very efficient sequential algorithms that generate irregular trees during the process of detecting shapes in images. These algorithms are based on the fast Hough transform and are used for solving the most complex stages of detection when the production of the parameters is uncoupled. However, the parallelization of these algorithms is complex, and the problem of load distribution is crucial. We present three parallel algorithms for solving this problem. One of the solutions employs static load balancing. The other two use dynamic balancing with two different control policies: distributed and centralized. These algorithms may also be used for solving other problems, such as the branch and bound, that generate irregular trees