Image Segmentation Based on Partial Differential Equation and Watershed Algorithm
NING Ji-Feng1,2, WU Cheng-Ke1, JIANG Guang1, YANG Shu-Qin2
1.National Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 7100712.
College of Information Engineering, Northwest A&F University, Yangling 712100
An image segmentation method is presented based on the partial differential equation to construct a good watershed structure for gradient level image and improve watershed segmentation. Firstly, the gradient level of the original image is obtained by edge detecting. Then the edge map of the gradient image is gradually diffused and the noises are removed by using 1D-GVF (gradient vector flow) partial differential equation. Thus the processed gradient level image has a good watershed structure. Furthermore, the local minima of the processed gradient level image are detected. Then the adjacent local minima are automatically merged by morphological dilation operation and consequently the image is favorable to the segmentation of watershed algorithm. Finally, the processed gradient level image is segmented by using watershed algorithm. Experimental results show the proposed method significantly decreases the over-segmentation and provides a reliable basis for further processing.
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2008, Vol. 21 
