quantification of surface defects using primary highlight in diffuse angle gray scale images

118 Pages·2016·2.69 MB·English

by  Subburengan Ganapathiraman

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University of Kentucky Master's Theses Graduate School
2005
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Subburengan Ganapathiraman
University of Kentucky, [email protected]
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Ganapathiraman, Subburengan, "QUANTIFICATION OF SURFACE DEFECTS USING PRIMARY HIGHLIGHT
IN DIFFUSE ANGLE GRAY SCALE IMAGES" (2005). University of Kentucky Master's Theses. 348.
https://uknowledge.uky.edu/gradschool_theses/348
This Thesis is brought to you for free and open access by the Graduate School at UKnowledge. It has been
accepted for inclusion in University of Kentucky Master's Theses by an authorized administrator of UKnowledge.
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ABSTRACT OF THESIS

QUANTIFICATION OF SURFACE DEFECTS USING PRIMARY
HIGHLIGHT IN DIFFUSE ANGLE GRAY SCALE IMAGES

The thesis presented is an effort to gather all possible information of one particular type
of common paint defect – the seed defect, from gray scale images of highly specular
painted surface. The proposed approach in the thesis utilizes a white light source to
illuminate the surface and utilizes a camera to capture its gray scale image at different
diffused angles. While attempting to explain the physics of highlight formation in terms
of location on the surface of a seed defect, the thesis also extends to utilize this
information from gray scale images to accurately predict the parameters of seed defects
including the height, size and position in real time. Since the primary highlight in a gray
scale image is more defined, contrary to the past researches on diffuse angle images that
use both primary / seed highlight and mirror highlight to estimate height of the seed, this
thesis formulates a theory of highlight translation and estimates the height of seed based
on primary / seed highlight. The other common type of surface defect - crater defect, is
also addressed in the thesis.

KEYWORDS: Specular reflection, Highlight translation, Gray scale images, Diffuse
angle reflection

Subburengan Ganapathiraman

December 12, 2005.

Copyright © Subburengan Ganapathiraman 2005.
QUANTIFICATION OF SURFACE DEFECTS USING PRIMARY
HIGHLIGHT IN DIFFUSE ANGLE GRAY SCALE IMAGES

By

Subburengan Ganapathiraman

Dr. Johné M. Parker
(Director of Thesis)

Dr. George Huang
(Director of Graduate Studies)

December 12, 2005
RULES FOR THE USE OF THESES

Unpublished theses submitted for the Master’s degree and deposited in the University of
Kentucky Library are as a rule open for inspection, but are to be used only with due
regard to the rights of the authors. Bibliographical references may be noted, but
quotations or summaries of parts may be published only with the permission of the
author, and with the usual scholarly acknowledgments.

Extensive copping or publication of the thesis in whole or in part also requires the
consent of the Dean of the Graduate school of the University of Kentucky.

A library that borrows this thesis for use by its patrons is expected to secure the signature
of each user.

Name Date
THESIS

Subburengan Ganapathiraman

The Graduate School

University of Kentucky

2005
QUANTIFICATION OF SURFACE DEFECTS USING PRIMARY
HIGHLIGHT IN DIFFUSE ANGLE GRAY SCALE IMAGES

______________________________

THESIS
______________________________

A thesis submitted in partial fulfillment of the requirements
for the degree of Master of Science in Electrical Engineering at
the University of Kentucky

By

Subburengan Ganapathiraman

Lexington, Kentucky

Director: Dr. Johné M. Parker, Associate Professor
Mechanical Engineering, Lexington, Kentucky

2005
DEDICATION

To my Parents, Sister and Dhana
ACKNOWLEDGEMENT

Firstly, I would like to extend my sincere gratitude to my advisor Dr. Johné M. Parker for
her untiring support, co-operation and guidance in this project. Words are short to
describe her unbelievable energy level she brings to table during work and even
afterwards. Her support and insightful advice were highly valuable during my period as a
Graduate student.

I would also like to thank Dr.Jawahir and Dr.Khraisheh for agreeing to take part in my
committee and provide their valuable insight.

This work would not have been possible without the support and suggestions from my lab
mates Pradeep, Chen, Li, Yew Lim and Joe. I take this opportunity to thank each and
every one of them.

I would also like to extend my sincere thanks to my friends who have in some way or
other been helpful to my thesis.

Finally, the acknowledgement would not be complete if I don’t mention my family for
their love, support and encouragement. I thank every one of them.

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TABLE OF CONTENTS

ACKNOWLEDGEMENT iii
LIST OF TABLES vii
LIST OF FIGS viii
CHAPTER 1: INTRODUCTION
1.1 Motivation 1
1.2 Thesis outline 3
CHAPTER 2: LITERATURE REVIEW AND TECHNICAL BACKGROUND
2.1 Current Inspection systems 4
2.2 Reflectance model 7
2.3 Camera Model 9
CHAPTER 3: SMALL SCALE EXPERIMENTAL SETUP
3.1 Construction 10
3.2 Initial adjustments in Setup 12
3.3 Capturing images using small scale setup 15
3.4 Images from diffuse angles 16
CHAPTER 4: THEORY OF HIGHLIGHT FORMATION
4.1 Theory behind images obtained from specular and diffused angle 17
4.2 Phenomenon of highlight formation in near spherical seed defects 19
4.3 Location of highlight spot on surface of a seed defect 22

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CHAPTER 5: EXPERIMENTS ON HIGHLIGHT TRANSLATION AND SEED
DEFECT QUANTIFICATION
5.1 Correction factor for seed height 29
5.2 Highlight translation on a 2-D plane 31
5.2.1 Estimating seed size using highlight translation 33
5.2.2 Relation between translation distance & size of seed defect 35
5.2.3 Approximation of translation distance 37
5.3 Quantifying radius of seed defect 38
5.4 Position of seed defect in real world co-ordinate 44
5.4.1 Aliter for seed location from seed and mirror highlight 46
CHAPTER 6: INVESTIGATION ON CRATER DEFECTS
6.1 Studies on simulated crater defects 48
6.1.1 Light at 30° and Camera at 50° 49
6.1.2 Light at 30° and Camera at 65° 50
6.1.3 Light at 30° and Camera at 70° 50
6.2 Conclusions from Images
CHAPTER 7: RESULTS AND DISCUSSIONS
7.1 Correction factor for computed height using single image 54
7.2 Seed height estimation using highlight translation 56
7.3 Location of seed in view space 64
7.4 Radius of seed defect 68

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