This work discusses an improvement to the boundary tracking algorithm introduced by Chen et al 2011. This method samples points in an image locally and utilizes the CUSUM algorithm to reduce tracking problems due to noise or texture. However, when tracking problems do arise, the local nature of the algorithm does not give any mechanism in which to recover. This work introduces a second CUSUM algorithm to detect off-boundary movement, compensating for such movement by backtracking. Boundary tracking results comparing the two algorithms are presented, including both image data and a numerical comparison of the effectiveness of the algorithms.

Date Published: 8 November 2012
PDF: 7 pages
Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85370E (8 November 2012); doi: 10.1117/12.974692

Published in SPIE Proceedings Vol. 8537:
Image and Signal Processing for Remote Sensing XVIII
Lorenzo Bruzzone, Editor(s)