Fast circle detection algorithm using Sequenced Hough Transform

To solve the problem of low hit ratio of random sampling in the same circle and complexity of voting process when Randomized Hough Transform (RHT) or its improved algorithm were used to detect circles, an algorithm for fast circle detection using Sequenced Hough Transform (SQHT) was proposed. It used the geometric features and gradient direction information of a circle to sequentially search the circle edge points sets and turned the acquisition of circle parameters based on vote of RHT to a discussion of locating three points of circle effectively. By using the method, the first edge point was searched sequentially and its gradient was calculated based on the adjacent edge point set or its gray value. The second point was mapped according to gradient of the first point in the row. The third point was mapped according to the information of two points above. The true circle parameters were finally calculated by RHT method, which avoids timing uncertainty caused by randomness of sampling. This method has features of high speed, controllable detection time, wide range of application and strong anti-interference performance. Comparing with the RHTs, experimental results indicate that the proposed algorithm can improve 2 times or more in the image of single circle, and 5 times or more in the image of multi-circles (5 or more). It can efficiently remedy the shortage of RHT in multi-circle detection.