King Saud University Repository >
King Saud University >
Science Colleges >
College of Computer and Information Sciences >
College of Computer and Information Sciences >

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

Files in This Item:

File Description SizeFormat
drAli_11_Conf.doc34 kBMicrosoft WordView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


DSpace Software Copyright © 2002-2009 MIT and Hewlett-Packard - Feedback