diff --git a/README.md b/README.md
index aee8b26..aeffb03 100644
--- a/README.md
+++ b/README.md
@@ -1,15 +1,15 @@
# Table of Contents
-1. [A Gentle Introduction](#orgf9d4f1c)
- 1. [Lecture Information](#org33b5f32)
- 1. [Assignments](#orgf7e9b9e)
- 2. [The Lecture Structure](#orgb5cae0e)
- 3. [Code Supplement](#org94a0f06)
- 4. [Reading List](#org159a80f)
+1. [A Gentle Introduction](#org6bdbe1a)
+ 1. [Lecture Information](#orga66fad8)
+ 1. [Assignments](#org8ab78d2)
+ 2. [The Lecture Structure](#org6649915)
+ 3. [Code Supplement](#org1715c47)
+ 4. [Reading List](#orgddf167e)
-
+
# A Gentle Introduction
@@ -22,7 +22,7 @@ focus will be on the topics of:
4. An example of using ML in image recognition techniques.
-
+
## Lecture Information
@@ -118,7 +118,7 @@ The details of the lecture are given below.
-
+
### Assignments
@@ -161,135 +161,135 @@ The grade breakdown is as follows:
-1. Individual Assignment
-
- An individual assignment will be given to you to work on. This assignment will consist of
- questions pertaining to concepts and image processing techniques.
-
- The grade breakdown is as follows:
-
-
-
-
-
-
-
-
-
-
-
- DEFINITION |
- GRADE (%) |
-
-
-
-
-
- Report Style |
- 15 |
-
-
-
-
- Q1 - Blurring Filters |
- 15 |
-
-
-
-
- Q2 - Image Channel Analysis |
- 15 |
-
-
-
-
- Q3 - RNG Map Generation |
- 10 |
-
-
-
-
- Q4 - Image Cleaning |
- 10 |
-
-
-
-
- Q5 - Shape Recognition |
- 30 |
-
-
-
-
- Q6 - Image Quality Comparison |
- 10 |
-
-
-
-
- Sum |
- 100 |
-
-
-
-
- **NOTE:** The assignment is individual and is not meant to be worked as a group. Once the
- code and the work is submitted it will be vetted against a software to determine
- if any collusion has occured.
-
-2. Group Assignment
-
- The group assignment focuses on a student defined project which its presentation will be
- done in the last 3 sessions of the course. You are to come up with a group and a project
- within the first 3 weeks of the lecture otherwise one will be given to you.
-
- The grade breakdown is as follows:
-
-
-
-
-
-
-
-
-
-
-
- DEFINITION |
- GRADE (%) |
-
-
-
-
-
- Report Style |
- 15 |
-
-
-
-
- Content |
- 55 |
-
-
-
-
- Q & A |
- 30 |
-
-
-
-
- In report writing students must declare their contribution to the work and they will be
- asked regarding their field of work during the Q&A (i.e., if Student A has worked with
- blurring filter he may be asked on why a specific one is chosen and/or the concepts and
- maths behind the said filter).
-
- **NOTE:** Students will be graded based on their contribution to the project and answers
- during the Q&A, therefore will be graded individually.
-
-
-
+**Individual Assignment**
+
+An individual assignment will be given to you to work on. This assignment will consist of
+questions pertaining to concepts and image processing techniques.
+
+The grade breakdown is as follows:
+
+
+
+
+
+
+
+
+
+
+
+DEFINITION |
+GRADE (%) |
+
+
+
+
+
+Report Style |
+15 |
+
+
+
+
+Q1 - Blurring Filters |
+15 |
+
+
+
+
+Q2 - Image Channel Analysis |
+10 |
+
+
+
+
+Q3 - RNG Map Generation |
+10 |
+
+
+
+
+Q4 - Image Cleaning |
+10 |
+
+
+
+
+Q5 - Shape Recognition |
+30 |
+
+
+
+
+Q6 - Image Quality Comparison |
+10 |
+
+
+
+
+Sum |
+100 |
+
+
+
+
+**NOTE:** The assignment is individual and is not meant to be worked as a group. Once the
+code and the work is submitted it will be vetted against a software to determine
+if any collusion has occured.
+
+**Group Assignment**
+
+The group assignment focuses on a student defined project which its presentation will be
+done in the last 3 sessions of the course. You are to come up with a group and a project
+within the first 3 weeks of the lecture otherwise one will be given to you.
+
+The grade breakdown is as follows:
+
+
+
+
+
+
+
+
+
+
+
+DEFINITION |
+GRADE (%) |
+
+
+
+
+
+Report Style |
+15 |
+
+
+
+
+Content |
+55 |
+
+
+
+
+Q & A |
+30 |
+
+
+
+
+In report writing students must declare their contribution to the work and they will be
+asked regarding their field of work during the Q&A (i.e., if Student A has worked with
+blurring filter he may be asked on why a specific one is chosen and/or the concepts and
+maths behind the said filter).
+
+**NOTE:** Students will be graded based on their contribution to the project and answers
+during the Q&A, therefore will be graded individually.
+
+
+
## The Lecture Structure
@@ -432,7 +432,7 @@ methods in improving/analysing gathered images. The structure of the lecture is
-
+
## Code Supplement
@@ -442,7 +442,7 @@ it is not feasible to fit all the content of the code to the slides and it is ea
[Visit the Code Supplement Website](https://dtmc0945.github.io/L-MCI-BSc-Digital-Image-Processing/)
-
+
## Reading List
@@ -456,5 +456,3 @@ mandatory.
3. Nixon M. et. al "Feature Extraction and Image Processing for Computer Vision" Academic press 2019
4. Gonzalez R. "Digital Image Processing" Pearson 2009.
-**White Papers**
-