Distance maps from unthresholded magnitudes

A straightforward algorithm that computes distance maps from unthresholded magnitudes is presented, suitable for still images and video sequences. While results on binary images are similar to classic Euclidean Distance Transforms, the proposed approach does not require a binarization step. Thus, no thresholds are needed and no information is lost in intermediate classification stages. Experiments include the evaluation of spatial and temporal coherence of distance map values, showing better results in both measurements than those obtained with Sobel or Deriche gradients and classic chessboard distance transforms.

► New method to compute distance maps from unthresholded magnitudes.
► Suitable for still images and real time applications.
► Better region-to-error ratio in a watershed segmentation.
► Higher stability in video sequences.
► It can be easily reproduced following the proposed algorithm.