Bioinformatics
Lecture 1
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Assessment
Total: 100 marks
• Final Exam: 60 marks
• Mid-term: 20 marks
• Quiz: 5 marks
• Oral : 5 marks
• Project: 10 marks
You will pass if you get 50 marks (PASS)
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Grades
التقدير الرمز عدد النقاط الدرجة
ممتاز A+ 4 90فأكثر
A 3.7 85إلى أقل من 90
جيد جدا B+ 3.3 80إلى أقل من 85
B 3 75إلى أقل من 80
جيد C+ 2.7 70إلى أقل من 75
C 2.4 65إلى أقل من 70
مقبول D+ 2 60إلى أقل من 65
D 1.7 50إلى أقل من 60
راسب F 0 أقل من 50
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Levels
• Level 1: Credit Hours < 30
• Level 2: 30 ≤ Credit Hours < 65
• Level 3: 65 ≤ Credit Hours < 102
• Level 4: Credit Hours ≥ 102
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Course Content
• Chapter 1: Common Biological Signals and Patterns
- 1.1 Fingerprint
- 1.2 Electrocardiogram (ECG)
- 1.3 Photoplethysmogram (PPG)
- 1.4 Blood Oxygen Saturation (SpO2)
- 1.5 Heart Rate
- 1.6 Respiration Rate
- 1.7 Face recognition
- 1.8 Electroencephalogram (EEG)
- 1.9 Electromyography (EMG)
- 1.10 Electrooculogram (EOG)
• Chapter 2: Biological Signal Processing
• Chapter 3: DNA Sequencing
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Fingerprint
Fingerprints are one of the many unique biometric signatures which
we can use to identify people very accurately.
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Fingerprint Nature
• The skin on the palms of our hands has a special pattern called friction
ridges that help us grab things effectively without slipping.
• These patterns consist of ridges and valleys arranged in certain
configurations and is unique for each individual.
• When a finger comes in contact with a surface, the ridges make strong
contact with the surface. When we strongly grab something, the moisture,
grease, dirt, and dead skin cells on our finger can attach to the surface of
the material, leaving an impression we call a fingerprint.
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Fingerprint Lifting
Various forensic methods involving
the use of chemicals are used to
extract such fingerprints from crime
scenes.
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Fingerprint Characteristics
Human fingerprints are:
• unique
• difficult to alter
• durable over the life of an individual
• They are suitable as long-term markers of human identity.
• They may be employed by police to identify individuals who are suspicious
in crimes, or to identify people who are deceased and thus unable to
identify themselves, as in the aftermath of a natural disaster.
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Fingerprint Identification
Known as dactyloscopy
Dactyloscopy is the process of comparing
two instances of human fingerprints to
determine whether these fingerprints could
have come from the same individual.
No two fingerprints are ever exactly alike in
every detail; even two impressions
recorded immediately after each other from
the same hand may be slightly different.
Fingerprint identification involves an
expert, or expert computer system
operating under threshold scoring rules,
determining whether two friction ridge
impressions are likely to have originated
from the same finger or palm.
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Fingerprint Identification Dawn
In the early 19th century, people started to
realize that no two persons have exactly the
same pattern of fingerprints , even in the case
of identical twins.
These patterns are formed during the 12th
week of gestation and remain permanent
throughout the life.
Sir Francis Galton first introduced the
technique of comparing prints found at a
crime scene with those of the suspect.
Sir Edward Henry developed the system of
classifying fingerprints that was first adopted
as the official system in England which
eventually spread throughout the world. 11
Fingerprints have Three Patterns
Edward Henry recognized that fingerprints
have three basic patterns:
5% 60–65 % 30–35 %
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Fingerprint Patterns
Arch: The ridges enter from one side of the
finger, rise in the center forming an arc, and
then exit the other side of the finger.
Loop: The ridges enter from one side of a
finger, form a curve, and then exit on that
same side.
Whorl: Ridges form circularly around a
central point on the finger.
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Fingerprint as Biometric (biological password)
If you compare a fingerprint with a key, you can say that you actually have ten
keys in a person’s hands, as each fingerprint is different.
The fingerprint is a very certain method for identifying a person.
Compared with other methods of identification, such as a key, access card,
numerical code or a password, the fingerprint is very secure. You cannot lose
or forget it, and it cannot be stolen.
Fingerprint systems are cost effective. In extensive systems, such as access
control in factories, there is no need for cards or keys that need to be
distributed, collected back again, or removed from the register due to lost cards
or keys.
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Modern Fingerprint Sensors
A fingerprint sensor is an electronic device used to
capture a digital image of the fingerprint pattern.
The captured image is called a live scan.
This live scan is digitally processed to create a biometric
template (a collection of extracted features) which is
stored and used for matching.
Many technologies have been used including optical,
capacitive, ultrasonic, and thermal.
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Fingerprint Sensor Types
Optical scanners take a visual image of the fingerprint
using a digital camera.
Capacitive scanners use capacitors to form an image of
the fingerprint. This type is commonly used in mobile
phones fingerprint sensors.
Ultrasonic fingerprint scanners use high frequency sound
waves to penetrate the epidermal (outer) layer of the skin
to form an image of the fingerprint.
Thermal scanners sense the temperature
differences on the contact surface, in between
fingerprint ridges and valleys. 16
Fingerprint Identification
Identification is performed in four steps:
1. A picture is taken of the fingerprint.
2. The fingerprint is then transformed into a numerical model which
stores the fingerprint’s unique features and characteristics.
3. A recognized numerical model is compared with other numerical
model (or models) stored in the memory of the device to find
similarities and determine the degree to which they match.
4. The final decision is taken based on a threshold value for the
similarity level between the current model and the stored models. If
the similarity level is above the threshold value, the current model is
accepted, otherwise, it will be rejected.
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Identification Threshold
The threshold value determines the security level of
the fingerprint sensor.
If you put the threshold level at high value, the
device accepts only the models with higher values
of similarities (more secure).
On the other hand, if the threshold level is set at
low value, any model with a bit similarity with the
stored models can be accepted as one of trusted
models (less secure).
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Fingerprint Matching
Fingerprints are matched by one (or both) of two approaches:
microscopic and macroscopic.
The microscopic approach is called minutia matching.
The two minutia types are a ridge ending and bifurcation
Ending is a feature where a ridge terminates.
Bifurcation is a feature where a ridge splits from a single
path to two paths at a Y-junction.
An approximate number of minutiae found in the
fingerprint is from 10 to 100.
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Fingerprint Matching: microscopic
Each minutia is attributed with some features.
The features assigned for each minutia are: type, location (x, y), and
direction.
A minutia template constitutes all minutiae features inside the fingerprint.
All minutiae templates are stored in a memory.
At the verification stage, the template needed to be verified is compared
against templates inside the memory,
A matching score is obtained based on the amount of similarities between
the verified template and the templates in the memory.
The matching score is a range between 0 and 100 (or 255 based on the
classifier). Higher matching score indicates higher confidence in a match.
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Fingerprint Matching: macroscopic
The macroscopic approach is called global pattern matching.
In this approach, the flow of ridges is compared at all locations between a
pair of fingerprint images.
The ridge flow constitutes a global pattern of the fingerprint.
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Application (1)
Download 10 fingerprint images from a public repository and identify each
fingerprint as arch, loop, or whorl.
You can download fingerprint images from:
- https://www.kaggle.com/ruizgara/socofing
- https://www.kaggle.com/anujrai07/fingerprint-1
- https://www.mathworks.com/matlabcentral/fileexchange/52507-fingerprint-
color-image-database-v1
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Materials & Assignments
• Faculty Platform
• Google Classroom
Code:
ksrdbvd
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