A novel transform for curve detection, called the curve fitting Hough transform (CFHT), is proposed. In the conventional Hough transform (HT) and its variants, both storage and computation grow exponentially with the number of parameters. The CFHT is advantageous over the conventional HT and its variants in its high speed, small storage, arbitrary parameter range and high parameter resolution. This is achieved by fitting a segment of the curve to be detected to a small neighborhood of edge points. If the fitting error is less than a given tolerance, the parameters obtained from curve fitting are used to map an edge element to a single point in the parameter space. A multidimensional ordered parameter list is used to accumulate the presences of the curve to be detected. Most entries in the parameter list are 'useful' entries in the sense that they represent actual presences of the curves to be detected. Experimental results are presented.
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