Curvature Estimation and Description

• This paper presents a new method for detection and estimation of curvature. The algorithm is implemented in the hierarchical feature pyramid proposed in the GOP concept. Curvature is handled at the second level of the pyramid with a vector field description of the orientation of the image as input. This complex image is convolved with typically eight filters. The filter responses are combined into a description of curvature direction, curvature magnitude and curvature/linearity ratio. The procedure resembles in many ways the algorithms for the first level of the feature pyramid and seems to be a natural extension of these. The method is easy to implement and the tests made show that it performs well and can handle noisy conditions. Some comparisons with other algorithms have been carried out, and the results indicate that the methodology presented in this paper has a number of important advantages over other methods.

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