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http://hdl.handle.net/10553/46776
Title: | Distance maps from unthresholded magnitudes | Authors: | Antón-Canalís, Luis Hernández Tejera, Mario Sánchez-Nielsen, Elena |
UNESCO Clasification: | 1203 Ciencia de los ordenadores 120304 Inteligencia artificial |
Keywords: | Distance map Distance transform Pseudodistance |
Issue Date: | 2012 | Project: | Tecnicas de Visión Para la Interacción en Entornos de Interior Con Elaboración Mapas Cognitivos en Sistemas Perceptuales Heterogéneos. | Journal: | Pattern Recognition | Abstract: | 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. | URI: | http://hdl.handle.net/10553/46776 | ISSN: | 0031-3203 | DOI: | 10.1016/j.patcog.2012.02.010 | Source: | Pattern Recognition [ISSN 0031-3203], v. 45 (9), p. 3125-3130 |
Appears in Collections: | Artículos |
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