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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/15165

Title: An Image Segmentation Approach Based on Log-Normal Distribution
Authors: Ali El-Zaart
Hassan Mathkour
Keywords: Optical image segmentation, Thresholding, Log-Normal distribution, Split and Merge technique, and Homogeneity predicate test.
Issue Date: 2010
Abstract: image thresholding has a great importance in most image processing application due to its importance and effectiveness although its simplicity; it has a big issue in estimating the optimal threshold value for obtaining better segmentation quality. The objective of this study is to develop a thresholding method based on histogram Split-Merge technique and Log-Normal distribution. Using Log-Normal distribution to model histogram modes allow for better estimation of the threshold value. (Result) The proposed method is applied on different optical images. A good segmentation result is obtained. The experiment showed that the proposed method obtained very good results but it requires more testing on different types of images.
URI: http://hdl.handle.net/123456789/15165
Appears in Collections:College of Computer and Information Sciences

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