Application of SGNN-based method in image segmentation

Lu Li; Hong Jiang; Zhang Ren; Yong-fei Zhang

doi:10.1117/12.748753

15 November 2007 Application of SGNN-based method in image segmentation

Lu Li, Hong Jiang, Zhang Ren, Yong-fei Zhang

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67861Q (2007) https://doi.org/10.1117/12.748753
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, a SGNN (Self-Generating Neural Network)-based method is applied to image segmentation, which is implemented automatically by autonomously clustering the pixels according to their gray values. The optimization of SGNN is studied to further improve the accuracy and robustness, as well as to reduce the computational complexity of the segmentation. The experimental results show that the optimized SGNN gets better segmentation results and outperforms the existing methods for its distinguished advantages of perfect segmentation without any manual intervention, high self-learning capacity, less computational complexity, robustness to noise, etc. What's more, the experimental results suggest that the proposed method can be widely used in segmentation of all typical images, such as IR (Infrared) images, visible images, X-ray images, and MR (Magnetic Resonance) Images.

Citation Download Citation

Lu Li, Hong Jiang, Zhang Ren, and Yong-fei Zhang "Application of SGNN-based method in image segmentation", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861Q (15 November 2007); https://doi.org/10.1117/12.748753

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