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@inproceedings{631545, author = {Svoboda, David and Williams, Ian and Bowring, Nicholas and Guest, Elizabeth}, address = {Portugalsko}, booktitle = {First International Conference on Computer Vision Theory and Applications}, keywords = {edge detection; statistical tests; image analysis}, language = {eng}, location = {Portugalsko}, isbn = {972-8865-40-6}, pages = {457-462}, publisher = {INSTICC Press}, title = {Statistical techniques for edge detection in histological images}, year = {2006} }
TY - JOUR ID - 631545 AU - Svoboda, David - Williams, Ian - Bowring, Nicholas - Guest, Elizabeth PY - 2006 TI - Statistical techniques for edge detection in histological images PB - INSTICC Press CY - Portugalsko SN - 9728865406 KW - edge detection KW - statistical tests KW - image analysis N2 - A review of the statistical techniques available for performing edge detection on histological images is presented. The tests under review include the Student's T Test, the Fisher test, the Chi Square test, the Kolmogorov Smirnov test, and the Mann Whitney U test. All utilize a novel two sample edge detector to compare the statistical properties of two image regions surrounding a central pixel. The performance of the statistical tests is compared using histological biomedical images on which traditional gradient based techniques are not as successful, therefore giving an overall review of the methods, and results. Comparisons are also made to the more traditional Canny and Sobel, edge detection filters. The results show that in the presence of noise and clutter in histological images both parametric and non-parametric statistical tests compare well robustly extracting edge information on a series images. ER -
SVOBODA, David, Ian WILLIAMS, Nicholas BOWRING a Elizabeth GUEST. Statistical techniques for edge detection in histological images. In \textit{First International Conference on Computer Vision Theory and Applications}. Portugalsko: INSTICC Press, 2006, s.~457-462. ISBN~972-8865-40-6.
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