Evolution control of active contour and its application to ferrographic image segmentation
SONG Jia-sheng
DAI Le-yang
CHEN Dan
WANG Yong-jian
Abstract：In order to improve the efficiency of searching for the local minimum of edge features along an active contour (AC), and to speed up the segmentation of ferrographic images, a novel method is proposed based on the edge feature assessment and the evolution control of the AC. Firstly, the edge indicator (EI) function is calculated according to vector-valued images, and based on the calculation, the corresponding edge indicator field (EIF) is constructed for the active contour model (ACM) with more distinctive edge features. Secondly, an unscented Kalman filter of the AC’s EI is designed, and the filter is used to track and assess the AC’s edge features. Finally, based on the tracking and assessment process, the AC’s model parameters are adjusted to control the evolution of the AC adaptively. The parameters adjustment ensures that the ACM has different parameter setting in different image regions. Experimental results demonstrate that the proposed method significantly increase the convergence rate and control flexibility of active contour evolution model. And the application to ferrographic images shows the algorithm can accurately segment wear particles of different shapes. It not only avoids the leakage in weak image edges but also effectively removals false foreground, interference and noise.
Keywords：active contourlevel set methodimage segmentationunscented Kalman filter
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 832-839 )