Title :
The efficient algorithms for achieving Euclidean distance transformation
Author :
Shih, Frank Y. ; Wu, Yi-ta
Author_Institution :
Comput. Vision Lab., New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
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.
Keywords :
computational complexity; image processing; iterative methods; mathematical morphology; Euclidean distance transformation; digital binary image; iterative erosion algorithm; mathematical morphology; nonobject pixels; object image; object pixels; relative-coordinates recording; two-scan-based algorithm; Computer vision; Concurrent computing; Costs; Euclidean distance; Image converters; Image processing; Iterative algorithms; Iterative methods; Morphology; Pixel; Algorithms; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2004.826098