A fast image segmentation algorithm with local C V active contour model

For the typical C V Algorithm, there exists the weakness of requiring multi iterative operations and long time computation to deal with large size image. Based on the analysis upon the relationship between the image size and the initialized approaching image with the number of iterations and computing time to obtain the stead results, an improved local C V image divisional algorithm based on the segmentation of threshold value and the connected domain labeled algorithm to deal with large size image is proposed. The OTSU method is used to divide the threshold value of image to reach the goal of label and local segmentation of image through the fast non recursion algorithm of connected domains. The segmented pieces and the result of its segmentation are used as the initialized approaching image of the C V algorithm model. Compared with the classical C V algorithm, the analysis and simulated result indicates that the improved C V algorithm reaches the steady solution quickly with fewer times of iterations. The proposed method can handle large size image with profound contour details quickly and effectively.

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