Linear time Euclidean distance transform algorithms

التفاصيل البيبلوغرافية
العنوان: Linear time Euclidean distance transform algorithms
المؤلفون: Michael Werman, Joseph Gil, Heinz Breu, David G. Kirkpatrick
المصدر: IEEE Transactions on Pattern Analysis and Machine Intelligence. 17:529-533
بيانات النشر: Institute of Electrical and Electronics Engineers (IEEE), 1995.
سنة النشر: 1995
مصطلحات موضوعية: Applied Mathematics, Binary image, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Weighted Voronoi diagram, Euclidean distance, Computational Theory and Mathematics, Artificial Intelligence, Computer Science::Computer Vision and Pattern Recognition, Power diagram, Computer Vision and Pattern Recognition, Voronoi diagram, Centroidal Voronoi tessellation, Time complexity, Distance transform, Algorithm, Software, Mathematics
الوصف: Two linear time (and hence asymptotically optimal) algorithms for computing the Euclidean distance transform of a two-dimensional binary image are presented. The algorithms are based on the construction and regular sampling of the Voronoi diagram whose sites consist of the unit (feature) pixels in the image. The first algorithm, which is of primarily theoretical interest, constructs the complete Voronoi diagram. The second, more practical, algorithm constructs the Voronoi diagram where it intersects the horizontal lines passing through the image pixel centers. Extensions to higher dimensional images and to other distance functions are also discussed. >
تدمد: 0162-8828
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::dcc7117896c9dfdebfbddcce3055da93
https://doi.org/10.1109/34.391389
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........dcc7117896c9dfdebfbddcce3055da93
قاعدة البيانات: OpenAIRE