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Abbas Cheddad, Joan Condell, Kevin Curran and Paul Mc Kevitt Intelligent Systems Research Centre Faculty of Computing and Engineering University of Ulster United Kingdom Emails: cheddad-a [ AT ] email.ulster.ac.uk Web: http://www.infm.ulst.ac.uk/~abbasc/. Presentation Outline.

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Abbas Cheddad, Joan Condell, Kevin Curran and Paul Mc Kevitt

Intelligent Systems Research Centre

Faculty of Computing and Engineering

University of Ulster

United Kingdom

Emails: cheddad-a [ AT ] email.ulster.ac.uk

Web: http://www.infm.ulst.ac.uk/~abbasc/

introduction
Introduction
  • Segmentation techniques can be classified into two categories: boundary-based techniques and region-based techniques.
  • Region-based algorithms include region growing, region splitting and region merging
  • k-meansminimize the mean squared distance from each data point to its nearest center (k)
  • Dynamic thresholding determined by examining repetitively the minima between two peaks in the bi-model image histogram
  • Edge detection Sobel, Prewitt, Laplacian, and Canny
  • Voronoi Diagram (VD)based on selected feature points residing along the image edges of high gradient magnitude (M. A. Suhail et al.andM. Burge and W. Burger)
introduction4
Introduction

Applications

Remote sensing

Vehicle and robot navigation

Medical imaging

Optical Character Recognition (OCR)

Skeletonization

Scene analysis

Shape reconstruction, etc

4

methodology
Methodology

Image segmentation remains a long-standing problem in computer

vision and has been found difficult and challenging for two main

reasons (Z. Tu and S. Zhu):

The fundamental complexity of modelling a vast amount of visual data that appears in the image is a considerable challenge

The intrinsic ambiguity in image perception, especially when it concerns the so-called unsupervised segmentation (e.g., a decision whereby a region cut is not a trivial task)

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methodology6
Methodology

Voronoi Diagram (VD): Given a set of 2D points, the Voronoi region for a point Pi is defined as the set of all the points that are closer to Pi than to any other points. The dual tessellation of VD is known as the Delaunay Triangulation (DT).

VD of four generators

VD of three generators

VD of two generators

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methodology7
Methodology

VD of n scattered generators

7

methodology8
Methodology

Various literature studies have tended to apply VD on the image

itself (after binarizing it and capturing its edges). This is usually

time consuming

Thus, VD is constructed from feature generators that result from

gray intensity frequencies. O (n log n), where n<=255

8

methodology9
Methodology

Voronoi Diagram in red and Delaunay Triangulations in blue applied on an image histogram

02/04/2014

9

Local flip effect on the histogram

conclusions
Conclusions

We have presented our novel algorithm for image segmentation based on points geometry derived from the image histogram

Our proposal shows less complexity while maintaining high performance

This work is a pre-processing phase for our ongoing research on adaptive digital image Steganography. The latter is the science of concealing confidential data in multimedia medium in an imperceptible way

12

contacts
Contacts
  • WWW: http://www.infm.ulst.ac.uk/~abbasc/
  • Email: cheddad-a [ AT ] email.ulster.ac.uk
  • Tel: +44 28 71375156

Thank you for listening…..

Questions?