@inproceedings{33bc98e22f754adb89abf6e96f21e4ce,
title = "An adaptive split-and-merge method for smoothing and compression of image contours",
abstract = "The contour of a digital image usually has a large number of edges and may suffer from quantization error and noise. In feature extraction or shape matching algorithms, contour smoothing must be performed to reduce noise and quantization error and to compress the data while still keeping its original shape. This study presents a split-and-merge method with adaptive tolerance value for smoothing image contours. The tolerance value depends on the grid constant D and the length of line L in collinearity tests. Experimental results on real binary contours show the method is very effective and precise for smoothing of binary image.",
author = "Yi Xiao and Zou, {Ju Jia} and Hong Yan",
year = "1999",
doi = "10.1109/ISSPA.1999.818117",
language = "English",
isbn = "1864354518",
series = "ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications",
publisher = "IEEE Computer Society",
pages = "79--82",
booktitle = "ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications",
note = "5th International Symposium on Signal Processing and Its Applications, ISSPA 1999 ; Conference date: 22-08-1999 Through 25-08-1999",
}