Abstract
Image segmentation can be defined as a cutting or segmenting process of the digital image into many useful points which are called segmentation, that includes image elements contribute with certain attributes different form Pixel that constitute other parts. Two phases were followed in image processing by the researcher in this paper. At the beginning, pre-processing image on images was made before the segmentation process through statistical confidence intervals that can be used for estimate of unknown remarks suggested by Acho & Buenestado in 2018. Then, the second phase includes image segmentation process by using "Bernsen's Thresholding Technique" in the first phase. The researcher drew a conclusion that in case of utilizing the statistical confidence intervals beside Bernsen's Thresholding technique it can give better results in image segmentation. This method is characterized with different performance if it is compared with the regular Bernsen's thresholding technique during the direct image segmentation in both cases,namely , in case of natural image status or adding speckle noise perturbation.
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