9 September 2017 Consistency functional map propagation for repetitive patterns
Author Affiliations +
J. of Electronic Imaging, 26(5), 053006 (2017). doi:10.1117/1.JEI.26.5.053006
Repetitive patterns appear frequently in both man-made and natural environments. Automatically and robustly detecting such patterns from an image is a challenging problem. We study repetitive pattern alignment by embedding segmentation cue with a functional map model. However, this model cannot tackle the repetitive patterns directly due to the large photometric and geometric variations. Thus, a consistency functional map propagation (CFMP) algorithm that extends the functional map with dynamic propagation is proposed to address this issue. This propagation model is acquired in two steps. The first one aligns the patterns from a local region, transferring segmentation functions among patterns. It can be cast as an L2,1 norm optimization problem. The latter step updates the template segmentation for the next round of pattern discovery by merging the transferred segmentation functions. Extensive experiments and comparative analyses have demonstrated an encouraging performance of the proposed algorithm in detection and segmentation of repetitive patterns.
© 2017 SPIE and IS&T
Hao Wang, "Consistency functional map propagation for repetitive patterns," Journal of Electronic Imaging 26(5), 053006 (9 September 2017). https://doi.org/10.1117/1.JEI.26.5.053006 Submission: Received 23 January 2017; Accepted 11 August 2017
Submission: Received 23 January 2017; Accepted 11 August 2017

Image segmentation

Detection and tracking algorithms

Image processing algorithms and systems


3D image reconstruction

Binary data

Volume rendering


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