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Proceedings Paper

Image segmentation by gradient statistics
Author(s): Kenong Wu; Steven Schreiner; Brent Mittelstadt; Leland Witherspoon
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Paper Abstract

This paper introduces a new gradient-based thresholding method for segmenting gray level images. This method first computes the magnitudes of image gradients. It, then, determines a range of threshold candidates from a statistic measure, called average of averaged gradients. Finally, it derives the image threshold from those candidates. The algorithm is fully automatic and does not analyze the shape of the image histogram. Unlike most gradient-based thresholding methods, this approach effectively reduces the influence of noise in both object and background regions to the threshold selection by computing the threshold from an intensity range, which corresponds only to the intensities at the boundary regions between the object and its background. It is more accurate and orders of magnitude faster than a similar approach. The experiments with synthetic images and real medical images are performed. Comparisons between this method and three other gradient- based approaches are conducted.

Paper Details

Date Published: 24 June 1998
PDF: 8 pages
Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); doi: 10.1117/12.310885
Show Author Affiliations
Kenong Wu, Integrated Surgical Systems, Inc. (United States)
Steven Schreiner, Integrated Surgical Systems, Inc. (United States)
Brent Mittelstadt, Integrated Surgical Systems, Inc. (United States)
Leland Witherspoon, Integrated Surgical Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 3338:
Medical Imaging 1998: Image Processing
Kenneth M. Hanson, Editor(s)

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