A fast Hough transform for circular object detection is proposed in this paper which can be directly applied to gray level images. This method consists of three major stages. In the first stage, the center positions of circular objects are detected using the gray level Hough transform, which requires no conventional preprocessing such as edge detecting and binarization. The second stage determines the radius of the detected objects by analyzing the radial gradient profile. In order to detect objects with different radius in the same scene, a multi-scale strategy is integrated in the proposed method. Compared with traditional Hough transform, the gray level Hough transform uses a 2-dimensional accumulation map rather than the 3-dimensional one, which results in a dramatic improvement on the computational efficiency. Experiments have been carried out on more than 2000 real-world images and the result shows that 90.3% of the circular objects have been accurately detected, which demonstrate the applicability of the proposed method.
Fuzzified Circular Gabor Filter for Circular and Near-Circular Object Detection
