Target Segmentation in Complex Environment Using Fractal Features

By analysis of the discrete fractal Brownian random field model, an intelligent segmentation algorithm is proposed to process targets in complex environment. Firstly, to smooth the rough background texture, four-direction gradients are extracted out for filter which would obviously reduce singular v...

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Bibliographic Details
Main Authors: Ding Su, Qiheng Zhang, Shenghua Xie
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
BP NN
Content addressable storage
Equations
Fractal
Fractals
Mathematical model
Multi-features
Neural networks
Optical control
Optical filters
Pattern recognition
Robustness
Segmentation
Smooth
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Summary:By analysis of the discrete fractal Brownian random field model, an intelligent segmentation algorithm is proposed to process targets in complex environment. Firstly, to smooth the rough background texture, four-direction gradients are extracted out for filter which would obviously reduce singular values with variable gray intensity distribution. Secondly, a new fractal parameter, named fractal modulation degree, is computed out to highlight immanent diversities of target and background. Then, passing through three-layer BP NN, multi-features are trained to obtain rational weight values and perform pattern recognition. Eventually, the contour of target is segmented out. Abundant experiments support the scheme's satisfying validity and reliability
DOI:10.1109/COGINF.2006.365680