Computer Science ›› 2018, Vol. 45 ›› Issue (2): 130-134.doi: 10.11896/j.issn.1002-137X.2018.02.023

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Fast Image Segmentation Method Based on Image Complexity through Curve Fitting

WANG Hai-feng, ZHANG Yi and JIANG Yi-feng   

  • Online:2018-02-15 Published:2018-11-13

Abstract: The classical Otsu algorithm,maximum entropy algorithm,and minimum cross entropy algorithm have poor segmentation image effect when image signal noise ratio (SNR) is low.The paper proposed a kind of image segmentation method based on image background and target object complexity from the perspective of the image complexity,greatly reducing redundancy with the curve fitting method and improving the real-time performance and stability of the algorithm.According to the experiment results,compared with the classical algorithm,the fast segmentation algorithm proposed in the paper has high operation speed,stability and reliability,and can effectively solve dissatisfactory image segmentation effect when image SNR is low.

Key words: Image complexity,Maximum entropy algorithm,Minimum cross entropy,Curve fitting,Image segmentation

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