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Abstract
En 中文
Introducing more information to improve the segmentation quality was regarded as an effective way, such as three-dimensional Otsu thresholding. However, it should be led to be very time consuming for real-time applications, and the Otsu criterion is questionable in some cases, for example, nondestructive testing. In the paper, a novel mechanism based on data field, originated from physical fields, is proposed for three-dimensional thresholding. Without any explicit criterions, an optimal threshold vector is produced using the self-adaptive evolution of data particles in the data field. And the proposed method has low time complexity. Experimental results, compared with the state-of-art algorithms and the related methods, suggest that the new proposal is efficient and effective. (C) 2012 Elsevier B.V. All rights reserved.
Keywords:
Data field
Image segmentation
Image thresholding
Three-dimensional thresholding
Entropy
Journal
IF:
6.5
Papers:
2.5W
Citations:
6.5W
Organization
Cited Papers
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