A new method of detecting features in Gaussian smoothed images is described. Applied to the simple case of marking the Canny edge pixels the method gives an improved response at comers where traditional methods have problems. Moreover, the method permits marking of more sophisticated features at essentially no extra cost. Additional information available includes local curvature estimates for each edge, direct (local) identification of occluded edges and marking and characterising comers on edges. The performance of the method on real images is compared with the Plessey-Harris corner detector. We find that the quality and sensitivity of these comer detection methods are similar, with the new method giving information on the orientation and opening angle of the corners. Finally it is shown how ellipse detection in noisy images is made possible using this curvature information.
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