Data field-based mechanism for three-dimensional thresholding

Authors:
Tao Wu;Kun Qin
Affiliations:
State Key Laboratory of Software Engineering,Wuhan University, Wuhan 430079, China and School of Information Science and Technology, Zhanjiang Normal University, Zhanjiang 524048, China;School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Venue:
Neurocomputing
Year:
2012

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Abstract

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.