Normal and tangent components normalization based GVF snake for image segmentation

Pengfei Zhai; Chengying Shi

doi:10.1117/12.2243860

29 August 2016 Normal and tangent components normalization based GVF snake for image segmentation

Pengfei Zhai, Chengying Shi

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 1003318 (2016) https://doi.org/10.1117/12.2243860
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

We propose a novel external force for active contours by normalizing normal and tangent components of the gradient vector flow (GVF) along a generalized edge within the iteration process. The normal and tangent components normalization based GVF (NTCN-GVF) is inspired by the CN-GGVF which normalizes the x- and y-components of the generalized GVF (GGVF) to strengthen the smaller downward component of the external force within the long and thin indentations (LTIs). However, the strengthening effect is sensitive to the orientation of LTIs and excessive in homogeneous areas. NTCN-GVF behaves like CN-GGVF along the edge and conventional vector-based normalized GVF in homogeneous areas. Consequently, the NTCN-GVF snake can capture differently orientated LTIs and preserve weak edges while maintaining other desirable properties of enlarged capture range and noise robustness. Finally, experimental results are presented to verify the effectiveness of the method.

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Pengfei Zhai and Chengying Shi "Normal and tangent components normalization based GVF snake for image segmentation ", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003318 (29 August 2016); https://doi.org/10.1117/12.2243860

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KEYWORDS

Diffusion

Image processing

Gaussian filters

Image segmentation

Solids

Binary data

Head

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