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MOTION ESTIMATION IN BRAIN TOPOGRABIC MAPS

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MOTION ESTIMATION IN BRAIN TOPOGRABIC MAPS

By

GOWRI GOPALAKRISHNAN

FINAL REPORT

Submitted to the Electrical

&

Electronics Engineering Programme in Partial Fulfilment of the Requirement

for the Degree

Bachelor of Engineering (Hons) (Eectrical

&

Electronics Engineering)

UNIVERSITI TEKNOLOGI PETRONAS Bandar Seri Iskandar

31750 Tronoh Perak Darul Ridzuan

©Copyright Sept 2011 by

Gowri Gopalakrishnan

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CERTIFICATION OF APPROVAL

MOTION ESTIMATION IN BRAIN TOPOGRAHIC MAPS

Approved:

Dr. Aamir Saeed Malik Project Supervisor

By

Gowri Gopalakrishnan

A project dissertation submitted to the Electrical

&

Electronics Engineering Programme

Universiti Teknologi PETRONAS in Partial fulfillment of the requirement for the

Bachelor ofEngineering(Hons) (Electrical

&

Electronics Engineering)

Universiti Teknologi PETRONAS Tronoh, Perak

Sept 2011

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CERTIFICATION OF ORIGINALITY

This is to certify that I am responsible for the work submitted in this project, that the original work is my own except as specified in the references and acknowledgments and the work contain

herein have not been undertaken or done by unspecified sources or person.

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ACKNOWLEDGEMENT

First and foremost, my utmost gratitude to God for giving me the strength and guidance to complete this research project successfully.

Secondly, I would like to extend my thanks to my dearest supervisor, Dr, Aamir Saeed Malik for his patience, support, motivation and undivided attention and supervision in guiding me through the project.

Moreover, I am deeply indebted to my project colleagues who had supported this project.

To my beloved family members, you have always been inspiration to me. Thank you for endless love and support.

Finally, I would like to thank everyone who has helped me indirectly or directly in completing this project.

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ABSTRACT

The objective of brain mapping is to advance knowledge in understanding the brain functions with its respective structures. Current technologies and advances in brain imaging technique using EEG (electroencephalogram) allows estimation of network connection which represents activity that occur in different structures of human brain. As the EEG procedure is

>imple and harmless, it is widely used to study the brain behavior and cognitive processes such

iS memory, language, emotions, sensation and alertness. In past study, ten healthy subjects (five female and five male) undergo an experiment consists of 200 trials. These trials include two

>timulus consist of X and 0 which appears randomly. Subjects required to respond to X and ignore

0.

Signals gained from these events evaluated as topographical properties of brain aetwork. Note that, only segment of interest will be plotted on topographic maps. In present research, these topographic maps will be used to study the behavior of the brain signals due to presence of stimulus. Motion estimation is an interesting analysis of tracking movement of signals around brain region. Currently, no proper motion estimation technology is available for this purpose. Development of motion estimation system allows us to observe and study

movements of brain signals. In this project, I've applied Full Search Algorithm on brain topographic. Movement of signals detected based on general matching criteria which will be further discussed in the literature review.

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TABLE OF CONTENT

ABSTRACT

LIST OF FIGURES LIST OF TABLES

CHAPTER 1 INTRODUCTION 1.1 Problem Statement 1.2 Objective

1.3 Scope of Study 1.4 Time Frame

CHAPTER2 LITERATURE REVIEW 2.1 Fnll Search Algorithm 2.2 Optical Flow Estimation

2.3 Other Block Matching Algorithms 2.4 General Brain Anatomy

CHAPTER3 METHODOLOGY . 3.1 Research Methodology 3.2 Project Activities

3.3 Description of Project Activities 3.4 Gantt Chart

ii

i

iv vii

1

1 1 2

3

4 4 8 11 14

20 20 21 23 30

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CHAPTER 4 RESULTS AND DISCUSSION 4.1 Preprocessing

4.2 Behavior of Brain Signals 4.3 Results and Analysis

CHAPTER 5 CONCLUSION REFERENCES

APPENDIX

iii

31 32

34

35

40

43 50

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LIST OF FIGURES

Figure 1 General Time Frame for the project 3

Figure 2 Sequence of images in a video 4

Figure 3 Example of current and reference frame 4

Figure4 Fotward Prediction 5

Figure 5 Distance between point A and point B 6

Figure 6 Quasi Euclidean mapping 7

Figure 7 Orders of Quasi Euclidean 7

Figure 8 Optical flow vector in a moving object in a video sequence Figure 9 Image from position (x,y) at timet has moved to 8

(x+ox,y+lly,t+llt)

Figure 10 Example of Optical Flow Estimation from 8

Figure 11 The Aperture issues 9

Figure 12 Search window for Full Search Algorithm specified 10 by window size p

Figure 13 Example of Three-step with reduction of step size 11

Figure 14 Example of Diamond Search 12

Figure 15 Relationship between sensory nerves and spinal cord 14

Figure 16 Anatomy of the Brain 14

Figure 17 The location of Diencephalon in the forebrain 15 Figure 18 The location of the Telencephalon in the forebrain 15

Figure 19 The midbrain which makes up a brain stem 16

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