Adaptive thresholding based on active surface

Thresholding is difficult for images with poor contrast or illumination, intensive noise and non-planar background. An active surface based adaptive thresholding algorithm is proposed in this paper. Derived from the idea of active contour models, an active surface model is used to estimate the background surface ofthe image. Subtraction ofthis active surface from the original image surface is to remove the influence of uneven background and poor illumination, and convert the problem to a global threshold one. Thus a proper choice of the global threshold will obtain a desirable binary result.

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