2D Euclidean distance transform algorithms: A comparative survey
ACM Computing Surveys (CSUR)
Analysis of Relevant Maxima in Distance Transform. An Application to Fast Coarse Image Segmentation
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Geodesic Methods in Computer Vision and Graphics
Foundations and Trends® in Computer Graphics and Vision
Euclidean distance transform of digital images in arbitrary dimensions
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
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Euclidean distance transformation (EDT) is used to convert a digital binary image consisting of object (foreground) and nonobject (background) pixels into another image where each pixel has a value of the minimum Euclidean distance from nonobject pixels. In this paper, the improved iterative erosion algorithm is proposed to avoid the redundant calculations in the iterative erosion algorithm. Furthermore, to avoid the iterative operations, the two-scan-based algorithm by a deriving approach is developed for achieving EDT correctly and efficiently in a constant time. Besides, we discover when obstacles appear in the image, many algorithms cannot achieve the correct EDT except our two-scan-based algorithm. Moreover, the two-scan-based algorithm does not require the additional cost of preprocessing or relative-coordinates recording.