A New Method for Solving Image Segmentation Problems using Global Optimization
Keywords:
Image Segmentation, Otsu algorithm, Global Optimization, Filled Function MethodAbstract
The modified Otsu method with the optimized Filled Function Method is applied in this study to the segmentation of image to establish the appropriate threshold value for segmenting a grayscale image, results were evaluated for some MIR and showed that the partitioning time decreased by almost %70 . and apply the value of Single Peak quality to the Ratio of Noise (PSNR), Error of the Mean Square (MSE), and The Ratio of Noise to Signal (SNR) evaluation criteria for MIR segmentation, results indicate that our method takes little time compared to the conventional OTSU approach, where the real time is used measured in seconds (sec) for the proposed approach and the other algorthms, side by side, without sacrificing hash accuracy.The cons of the huge account are the primary topic of this essay. Due to the old OTSU method's low efficiency, polynomial and Filled Functions method FFM are presented to OTSU. Combining the FFM search optimization algorithm yields the ideal threshold and speeds up computation, which enhances performance segmentation.
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