COURSE UNIT TITLE

: CONSTRUCTION MATERIALS CHARACTERIZATION BY IMAGE ANALYSIS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CIE 5104 CONSTRUCTION MATERIALS CHARACTERIZATION BY IMAGE ANALYSIS ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ALI TOPAL

Offered to

CONSTRUCTION MATERIALS
CONSTRUCTION MATERIALS
CONSTRUCTION MATERIALS

Course Objective

The aim of this course is to give the basic concepts of the most commonly used methods and procedures for image processing, enhancement, restoration, analysis and classification of construction materials. The emphasis of the course is on practical results for classification and characterization of materials by on a well illuminated image and by processing (e.g., feature enhancement, color correction, sharpening, warping, etc.) and analysis.

Learning Outcomes of the Course Unit

1   To specify required details to take a well illuminated image
2   To create image processing steps
3   To define the basic concepts of the most commonly used methods and procedures for image processing
4   Analysis of the processed images
5   Classification of the analysis results

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to the Course Image Formation Inside the Camera Projection and Sensitivity Sensitivity and Color Digital Image Formation Sampling Quantization (R,G,B) Parameterization of Full Color Images Grayscale Images Images as Matrices 1. Homework Assignment
2 Illuminating the Scene Imaging Methods and Sensor Systems CCD Cameras Camera configuration Camera lenses Frame grabber Image processing systems
3 Simple Processing operations Simple Image Statistics - Sample Mean and Sample Variance Simple Image Statistics Histogram Point Processing Image Segmentation Histogram Based Image Segmentation Histogram Equalization Histogram Matching - Specification Quantization 1. Homework submission
4 Image Representation Image Processing and Filtering ``Perceptual'' Image Processing Quantization and False Contours Image Halftoning Image Warping and Special Effects Median Filtering Oil Painting Sampling and Antialiasing Filters Noise Removal 2. Homework Assignment
5 Image Segmentation: Edge Detection Image Segmentation: Additional Algorithms Binary Mathematical Morphology Image Processing Applications on Construction Materials
6 Shape Acquisition and Pre-Processing Introduction to Shape Analysis Computational Shape Analysis Case Studies Introduction to Two-Dimensional Shapes Continuous Two-Dimensional Shapes Planar Shape Transformations Characterizing 2D Shapes in Terms of Features Classifying 2D Shapes Representing 2D Shapes Shape Operations Shape Metrics Morphological Transformations 2. Homework submission
7 Two-Dimensional Shape Representation Shape Characterization: Statistics for Shape Descriptors Some General Descriptors Fractal Geometry and Complexity Descriptors Curvature Fourier Descriptors Fourier Transforms and Gibbs Phenomenon Images and Edges Edge Detection Motivation Human Visual System and Match Bands 3. Homework Assignment
8 I.MIDTERM EXAM
9 Basic Mathematical Concepts: Linear Algebra Differential Geometry Multivariate Calculus Convolution and Correlation Probability and Statistics Fourier Analysis Principal Components Analysis Fisher's Linear Discriminant Analysis Shape Classification Pattern Classification Classification and Clustering A Case Study: Leaves Classification Evaluating Classification Methods 3. Homework submission
10 Image Processing and Analysis Programs: Qwin Plus Image Processing and Analysis Program UTHSCSA Imagetool MATLAB Image Processing and Analysis Toolboxes 4. Homework Assignment
11 Image Processing and Analysis Applications on Construction Materials Fluorescent Optic Microscopy Stereo Microscopy Stereoscopy with using CCD cameras SEM Analysis 4. Homework submission
12 Morphological Comparison of Bituminous Binders with Polymer Modified Bitumen Image Analysis Techniques for Classification of Aggregates in terms of Shape and Gradation 5. Homework Assignment
13 II.MIDTERM EXAM
14 Image Analysis Techniques for Characterization of Pore Structure of Cement-Based Materials Quantitative Assessment of Microcracks in Cement-Based Materials Binary segmentation of Aggregate in SEM Image Analysis of Concrete Three-Dimensional Shape and Surface Representation New Developments about 3D Imaging Techniques 3D Image Construction 5. Homework submission

Recomended or Required Reading

Textbook(s):

Roberto M. Cesar Jr, Luciano da Fontoura Costa (2001), Shape Analysis and Classification: Theory and Practice, CRC press Washington.

Mehta, P.K. Monteiro, P.J.M. (1999), Concrete: Microstructure Properties and Materials, Chennai, Indian Concrete Institute.

Supplementary Book(s):

Javidi, B. (2001), Image Recognition and Classification, Algorithm, Systems, and Applications, Marcel Dekker Inc., New York Bassel.

Gonzales, R.C., Woods, R.E., Eddins, S.L (2004), Digital Image Processing Using MATLAB, Pearson Ed. Int. Prentice Hall.

Erhardt, F. (2003), Theory and Applications of Digital Image Processing, University of Applied Sciences, Offenburg.

Hartley, R., Zisserman, A. (2002), Multiple View Geometry in Computer Vision, Cambridge Press

Planned Learning Activities and Teaching Methods

Course presentations, home-works and visual presentations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE 1 MIDTERM EXAM 1
2 MTE 2 MIDTERM EXAM 2
3 ASG ASSIGNMENT
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE 1 * 0.20 + MTE 2 * 0.20 + ASG * 0.10 + FIN * 0.50
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE 1 * 0.20 + MTE 2 * 0.20 + ASG * 0.10 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

LO 1-2-3: Consideration with mid-term exams and final exam
LO 4-5: Consideration with homework assignments

Language of Instruction

Turkish

Course Policies and Rules

Attendance will be considered in the evaluation.

Contact Details for the Lecturer(s)

Assoc.Prof.Dr. Ali TOPAL, ali.topal@deu.edu.tr

Office Hours

The course schedule will be announced by the faculty member is created.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Tutorials 0 0 0
Preparations before/after weekly lectures 12 5 60
Preparation for midterm exam 2 15 30
Preparation for final exam 1 18 18
Preparing assignments 5 8 40
Final 1 2 2
Midterm 2 2 4
Quiz etc. 0 0 0
TOTAL WORKLOAD (hours) 190

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.11
LO.22235
LO.31435
LO.43244
LO.5253

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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