Math @ Duke

Publications [#264927] of Guillermo Sapiro
Papers Published
 Olver, PJ; Sapiro, G; Tannenbaum, A, Affine invariant detection: Edge maps, anisotropic diffusion, and active contours,
Acta Applicandae Mathematicae, vol. 59 no. 1
(1999),
pp. 4577
(last updated on 2018/10/17)
Abstract: In this paper we undertake a systematic investigation of affine invariant object detection and image denoising. Edge detection is first presented from the point of view of the affine invariant scalespace obtained by curvature based motion of the image levelsets. In this case, affine invariant maps are derived as a weighted difference of images at different scales. We then introduce the affine gradient as an affine invariant differential function of lowest possible order with qualitative behavior similar to the Euclidean gradient magnitude. These edge detectors are the basis for the extension of the affine invariant scalespace to a complete affine flow for image denoising and simplification, and to define affine invariant active contours for object detection and edge integration. The active contours are obtained as a gradient flow in a conformally Euclidean space defined by the image on which the object is to be detected. That is, we show that objects can be segmented in an affine invariant manner by computing a path of minimal weighted affine distance, the weight being given by functions of the affine edge detectors. The gradient path is computed via an algorithm which allows to simultaneously detect any number of objects independently of the initial curve topology. Based on the same theory of affine invariant gradient flows we show that the affine geometric heat flow is minimizing, in an affine invariant form, the area enclosed by the curve.


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