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Image Processing

Course Code 006132 (Spring 2020)

Prof. S. M. Riazul Islam, Dept. of Computer Engineering, Sejong University, Korea

Introduction

E-mail: [email protected]

Introduction to Image Processing

Upon Completion of this content, we should understand

Course Information

Concept of a digital image.

Definition and scope of digital image processing.

Fundamentals of the electromagnetic spectrum and its relationship to imagegeneration.

Different fields in which digital image processing methods are applied.

Basic processes involved in image processing.

Components that make up a general-purpose digital image processing system.

Diverse Involvements of Image Processing!

X-ray MRI

Single Atom UniverseEarth Black Hole

Recording Memories

Speed CameraFacial Recognition Social Media

Galaxy

Spectacular Cosmos, Hubble/ESO telescope (HD space images)

New Use Cases Are Coming Continuously

https://www.weforum.org/agenda/2020/03/coronavirus-before-and-after?fbclid=IwAR273oNYYb4yt7Xch4FzVMsiGEnJkv-v_Tp5XxHX_HtwJa-P6QSY5q1ymgc

BEFORE: Tehran airport, Iran, Jan. 11, 2020. AFTER: Tehran airport, Iran, Feb. 29, 2020.

Satellite pictures show the impact of the Coronavirus

Image Processing

3 Credits Course

Lectures: 3 hours of lectures weekly

Monday 09.00 to 10.30

Wednesday 09.00 to 10.30

Type: Theory/Tutorial/Demonstration (Lectures)

Attendance: Please check Ucheck for attendance, absence and late rules

Attendance: 5 min before and 10 min after lecture starting

Late: 10 to 15 min after lecture starting

Absence: 15 min after lecture starting

Note: For online lecture time, attendance, and other regulations, see the notifications in Blackboard/online lecture posting

Image Processing

Assessment

Mid-term exam: 25%

Final exam: 25%

Assignment/Project: 40%

Practice Assignment (PA): 10%

Project: 30%

Attendance: 10%

Objective: Multiple choice, True/False, Matching, and Completion

Subjective: Short-answer essay, Extended-response essay, Problem solving.

The details of Assessment rubrics will be provided

Image Processing

Tentative project and Evaluation (Might be adjusted later on)

Report

Article reading

Submit a survey of the articles you read and the list of the articles.

Project

Submit an article including introduction, methods, experiments, results, and conclusions.

Submit the project code, the readme document, and some testing samples (images, videos, etc.) for validation.

Presentation

The details of Project and Assessment rubrics will be provided

Image Processing

Journals IEEE T IMAGE PROCESSING IEEE T MEDICAL IMAGING INTL J COMP. VISION IEEE T PATTERN ANALYSIS MACHINE INTELLIGENCE PATTERN RECOGNITION COMP. VISION AND IMAGE UNDERSTANDING IMAGE AND VISION COMPUTING … …

Conferences CVPR: Comp. Vision and Pattern Recognition ICCV: Int. Conf on Computer Vision ACM Multimedia ICIP SPIE ECCV: European Conf on Computer Vision CAIP: Intl Conf on Comp. Analysis of Images and Patterns … …

Image Processing

Course Materials

PDFs of slides

The slides are available in Blackboard of Sejong University

Sometimes the slides will be updated at a later date.

Also, for online lectures, the contents will be uploaded in Blackboard

Some more references and links for lectures notes maybe given from time to time

MATLAB

Some examples and the programming elements of the coursework will use MATLAB.

Image ProcessingSyllabus (1/3)

Intensity Transformations and Spatial Filtering

Introduction to DIP

Digital Image Fundamentals

Applications, Steps and Components.

Sensing & Acquisition, Sampling & Quantization,Representations, Mathematical Tools & Relationship.

Basic Intensity Transformations, Histogram Processing,Spatial Filter Fundamentals, Smoothing & Sharpening


Color Image Processing

Filtering in the Frequency Domain

Image Restoration and Reconstruction

Fourier Transform, Basics of Frequency Domain Filtering,Smoothing & Sharpening, Selective Filtering

Image Degradation Model, Noise Model, Restoration w. Noise, Noise Reduction, Inverse Filtering.

Color Models and Transformations, Smoothing & Sharpening.


Feature Extraction

Image Compression

Image Segmentation

Fundamentals, Lossless and Lossy compression.

Edge detection & Region Segmentation Techniques,Role of motions in segmentation.

Basic Concepts: Boundary, Region, and Principle Components

Image Processing

Contact

E-mail (Preferred):

[email protected]

[email protected]

Name/ID should be mentioned in any contact.

Office: 434 (AI Center)

A prior appointment through e-mail is recommended.

Image ProcessingE-mail Structure (7 Components)

To: [email protected]

Subject: Image Processing lecture/assignment/grade/project/exam/meeting

Dear Prof. Riazul Islam,

First introduce yourself with Name and ID.

Describe the issue in details.

Thank you.

Your Name and Details

1

2

3

4

5

6

7

mailto:[email protected]

Image Processing

Do Not Contact For:

Contact is just for missing information

Problem Solving.

Assignment Solving.

Understanding subject matter via e-mail.

All Lessons related matter will be discussed in the Class

Things to Follow

Assignment/HW via e-mail is not acceptable

Assessment rubrics (will be explained soon) will be followed to evaluate assignments/projects and exams.

University/Department rules and regulation must be followed.

Honesty will be appreciated.

More: Will be explained from time to time

Maximum number of permitted absence: 07 (seven) If the number of absence exceeds 7, FA grade will be assigned.

Image Processing

• Recommended Text Book

Other Books

The Digital Negative: Raw Image Processing in Lightroom, Camera Raw, and Photoshop, 2E (By By Jeff Schewe)

Effective for digital photographer’s.

Feature Extraction and Image Processing for Computer Vision, 3E (Mark Nixon)

Effective for people working with computer vision and image processing


What is Digital Image Processing?

Digital Image

— a two-dimensional function

x and y are spatial coordinates.

The amplitude of f is called intensity or gray level

at the point (x, y)

Pixel

— the elements of a digital image

(A digital image is composed of a finite number of elements, each of which has a particular location and value)

Digital Image Processing

— process digital images by means of computer.

It covers low-, mid-, and high-level processes.

( , )f x yX

Y


Digital Image Processing

Low-level: inputs and outputs are images (Ex: reduce noise, contrastenhancement, and image sharpening).

Mid-level: Outputs are attributes extracted from input images (Ex: partitioningan image into regions or objects, description of those objects to reduce themto a form suitable for computer processing, and recognition of individualobjects.)

High-level: An ensemble of recognition of individual objects (Ex: performingthe cognitive functions normally associated with human vision).

Overlap between image processing and image analysis is the area of recognition ofindividual regions or objects in an image.


Origins of Digital Image Processing

Sent by submarine cable between London and New York, the transportation time was reduced to less than three hours from more than a week


Origins of Digital Image Processing

In parallel with space applications, digital image processing techniques beganin the late 1960s and early 1970s to be used in medical imaging, remote Earthresources observations, and astronomy.

Introduction to Image ProcessingSources for Images

Main Sources: Electromagnetic (EM) energy spectrum;

Other Sources: Acoustic; Ultrasonic; Electronic; Synthetic images produced bycomputer

Negative Handprint Art


Major uses

Gamma-ray imaging: nuclear medicine and astronomical observations.

X-rays: medical diagnostics, industry, and astronomy, etc.

Ultraviolet: lithography, industrial inspection, microscopy, lasers, biologicalimaging, and astronomical observations.

Visible and infrared bands: light microscopy, astronomy, remote sensing, industry,and law enforcement.

Microwave band: radar.

Radio band: medicine (such as MRI) and astronomy.


Inject a patient with a radioactive isotope that emits gamma rays as it decays


The area in which the imaging system detected the plate

Results of automated reading of the plate content by the system


Synthetic Image

Some more names on Image Processing Applications

Banking Robotics & Automation

Simulation Training ForensicsMapping & GIS Logistics

Agriculture & Environment

Security & MonitoringMachine Learning


Fundamental Steps in DIP

Result is more suitable than the original

Improving the appearance

Extracting image components

Partition an image into its constituent parts or objects


Components of general-purpose image processing system

functions and recursion in...

Documents