Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1001
Title: Image segmentation by utilizing entropy concept
Authors: Sin, Chi-fai
Keywords: Image processing
Hong Kong Polytechnic University -- Dissertations
Issue Date: 2001
Publisher: The Hong Kong Polytechnic University
Abstract: In this thesis, the template matching approach is employed in image segmentation where the search for the best template is guided by an entropy criterion. The Grayscale Image Entropy (GIE) is used to evaluate the goodness of a given template against a grayscale image. Given a grayscale image, a template is postulated to approximate the true scene that gives rise to the grayscale image. For the grayscale image and the template, the GIE is calculated. It is shown that the greater the GIE value, the better would the template resemble the true scene. The template is then adjusted until the maximum GIE value is resulted. The template is the optimum segmented image in an entropy sense.
Based on the template matching approach and the maximum GIE criterion, three new image segmentation algorithms are proposed and investigated in this thesis. The first algorithm detects the boundary of the object in an image by evaluating the GIE value. It is shown that when the object in a template is at a position overlapping the true scene object boundary, the resultant GIE will be zero. By connecting all these zero GIE value points, the boundary of the true scene object can be detected and then the grayscale image segmented. The second and the third segmentation algorithms start with an initial template. Then the classification status of the template pixels adjusted either on a pixel-by-pixel or a block-by-block basis. Each adjustment would result in a new template and a new GIE value. Only those changes that lead to greater GIE value will be retained. After a series of adjustments made to the template, the optimum template that gives rise to the maximum GIE is obtained as the optimum segmented image. Segmentation results for synthetic and real images obtained in this thesis justify the approach.
Description: xi, 119 leaves : ill. (some col.) ; 30 cm.
PolyU Library Call No.: [THS] LG51 .H577M EIE 2001 Sin
URI: http://hdl.handle.net/10397/1001
Rights: All rights reserved.
Appears in Collections:Thesis

Files in This Item:
File Description SizeFormat 
b15650315_link.htmFor PolyU Users 167 BHTMLView/Open
b15650315_ir.pdfFor All Users (Non-printable)7.42 MBAdobe PDFView/Open
Show full item record

Page view(s)

786
Last Week
2
Last month
Checked on Jul 24, 2016

Download(s)

290
Checked on Jul 24, 2016

Google ScholarTM

Check



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