Active Canny: Edge Detection and Recovery with Open Active Contour Models

Muhammet Bastan, Syed Saqib Bukhari, Thomas Breuel

In: IET Image Processing Journal 11 12 Pages 1325-1332 IET 12/2017.


We introduce an edge detection and recovery framework based on open active contour models (snakelets) to mitigate the problem of noisy or broken edges produced by classical edge detection algorithms, like Canny. The idea is to utilize the local continuity and smoothness cues provided by strong edges and grow them to recover the missing edges. This way, the strong edges are used to recover weak or missing edges by considering the local edge structures, instead of blindly linking edge pixels based on a threshold.We initialize short snakelets on the gradient magnitudes orbinary edges automatically and then deformand grow them under the influence of gradient vector flow. The output snakelets are able to recover most of the breaks or weak edges and provide a smooth edge representation of the image; they can also be used for higher level analysis, like contour segmentation.

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz