TRIPLET CIRCULAR HOUGH TRANSFORM FOR CIRCLE DETECTION

A new method, triplet circular Hough transform, is proposed for circle detection in image processing and pattern recognition. In the method, a curve in an image is first detected. Next, a sequence of three points on the curve are selected, a sequence of parameters (a,b,r) corresponding to the three points are calculated by solving the circle equation of the curve, and two 2-D accumulators A(a,b) and R(a,b) are accumulated with 1 and r, respectively. Then the parameters {(a, b, r)} of the circles fitting the curve are determined from A(a,b) and R(a,b) by searching for the local maximum over A(a,b). Because no computation loops over center (a, 6) and/or radius r are needed, the method is faster than the basic and directional gradient methods. It needs also much smaller memory for accumulation.

A new method, triplet circular Hough transform, is proposed for circle detection in image processing and pattern recognition. In the method, a curve in an image is first detected.Next, a sequence of three points on the curve are selected, a sequence of parameters (a,b,r)corresponding to the three points are calculated by solving the circle equation of the curve, and two 2-D accumulators A(a,b) and R(a,b) are accumulated with 1 and r, respectively. Then the parameters {(a, b, r)} of the circles fitting the curve are determined from A(a, b) and R(a, b) by searching for the local maximum over A(a,b). Because no computation loops over center (a, b)and/or radius r are needed, the method is faster than the basic and directional gradient methods.It needs also much smaller memory for accumulation.