Identification
of Human based on Dental photograph or Dental radio graph is one of the popular
and emerging trends in Biometrics. The Dental biometric system utilize dental
photograph and dental radiograph  for
identification of person as it provide unique teeth feature such as crown,
bridges, fillings, and relative distance between neighboring teeth. For
implementation of a dental biometric system we have to implement various
Techniques such as Image enhancement, Segmentation, Feature extraction and
Matching. In this paper we try to make an effective system that identify person
based on their dental records.

 

Keywords: Ante
mortem (AM), Dental Biometrics, Dental Anatomy, Post mortem (PM)

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1. Introduction

Image processing is a
method to convert image into digital form by performing some operation on it,
in order to get some useful information or some enhanced features from it 16.
It is a type of Signal processing where input is image and output is image or
some characteristics features associated from it. Now a days image processing
is Rapidly Growing technology where lots of research  work is done in current trend. Image
processing basically include three basic steps: First is to importing Images
with the help of Optical scanner or digital photography. Second, is to
manipulate or analyse image by image enhancement or image compression. Third,
is output of image . 1

Image processing is used for many purpose like
visualization, image sharpening and restoration, Image retrieval, Measurement
of pattern , Image recognition. There are two types of image processing methods
Digital image processing and Analog image Processing. We focused on Digital
Image processing Methods and Techniques. Digital image processing refers to use of
computer algorithms and techniques to perform image processing on Digital
Images. An image may be defined as two dimensional function f (x ,y)
where x and y are Spatial coordinates and amplitude  f  at any pair of coordinates (x ,y) is called
intensity of the image. When x , y and the amplitude values of f are all
finite, discrete quantities, we call the image as digital image. 2

Biometric derived from the Greek word “bios”
for life and “metron” for to measure. A biometric system is used to identify
person based on their physical characteristics such as finger prints , teeth
pattern etc. A biometrics is a convenient and reliable method to identify human
identity. Biometrics system is divided in to two categories: Behavioural biometric
system and physiological or physical biometric system. Behavioural biometrics
is the field of study related to measure of uniquely identifying and measurable
patterns in human beings such as signature password. physiological or physical
biometrics is the field of study related to specific characteristics of humans
such as finger prints, iris patterns, face and palm print patterns. 3

 

 

Dental biometrics is also used in forensic
identification of human. Human Identification based on dental information was
first observed in Roman Empire when Nero’s mother Agripina ordered to kill
loilla paulina who was later identified by her dental caries and bad dental
condition.

The first treatise of human identification
based on dental records was done in 1857, by Dr Oscar Amoedo Valdes who applied
a dental based identification technique to identify disaster victim in Paris.
After his work human identification based on teeth is accepted worldwide. 4During
last decades human identification based on dental records was extremely used to
identify victims in massive disasters such as 9/11 terrorist attack in New york
and tsunami in Asia.

Dental Biometrics in Forensic identification of
human uses AM (anti mortem) and PM (post mortem) records in database for
matching Teeth patterns to identify human beings. Biometric features such as
finger print , face is destructed in accident such as plane crash, burning
accidents, floods ,so it is not possible to work with conventional methods so
in such case to identifying persons because bones and teeth does not easily
decay and it takes high temperature up to 1100 degree temperature for melting. 5

 

2. Dental Anatomy

  Dental Anatomy is a field of Anatomy which deals with study of human
tooth structure .It is also a taxonomical science that deals with naming teeth
& structures of teeth fig a. A Tooth (Teeth) is a small calcified whitish
structure found in the jaws (mouth) for breaking food. Tooth formation begins
before birth. Teeth are not made of bones but it is made of various types of
tissues, enamel etc. Teeth are hardest substance in human body. Different parts
of teeth are fig b:

1) CROWN: It is top part of tooth that we
normally see. Shape of crown determines tooth structure.

2) GUMLINE: In this Gum-line tooth and gums are
met. 

3) ROOT: It is a part of tooth which is
embedded in bone.

4) ENAMEL: It is outermost layer of teeth which
is hardest substance found in human body.

5) DENTIN: It is next layer of tooth found
after enamel.

6) PULP: It is the soft tissue found in the centre
of teeth.

Usually there are 20 primary (Baby) teeth and
28 to 32 permanent teeth, last 4are third molars or wisdom teeth each of which
may or may not grow in. Fig a shows that there are 16 teeth found in maxilla
(upper jaw) and 16 found in mandible (lower jaw). There are four types of teeth
they are:

1) INCISORS: sharp chisel shaped front teeth (4
upper and 4 lower) used for cutting.

2) CANINES: they are called cuspids because of
their shapes like cusps, used for tearing food.

3) PREMOLAR: these teeth have two cusps shape
for tearing and grinding.

4) MOLARS: These teeth have many cusps on their
biting surface and use for grinding food

                                  

                                                 
 Figure
a. Tooth Anatomy

                 

                                         
Figure b. Structure of tooth

 

 

3. Types of Dental
Radiograph

 

  Dental
radiographs are commonly called as X rays. A Dental radiographic image is
formed by a controlled burst of X ray radiation which penetrates oral
structures at different levels, depending on varying Anatomical densities,
before striking the film or sensor. Teeth appear lighter because less radiation
penetrates them to reach the film. Dental caries, infections and other changes
in the bone density appear darker because X ray readily penetrate these less
dense structures. Dental restorations (fillings, crowns) may appear lighter or
darker depending on the density of material. There are various types of dental
radio graph few of them are as follows 3:

 

1)
BITEWING: This technique involves biting down a special piece of paper so that
we can see the crowns of teeth. See (fig 1) 

                                    

                 

                                              Figure
1. Structure of tooth

2)
OCCLUSAL: This X ray is done when your jaw is closed to see how your upper and
bottom teeth line up.
See (fig 2) 

                                         

                                           
Figure 2. Structure of tooth

 

3)
PANORAMIC: In this type of radiograph the machine rotates around the head.
See (fig 3) 

                                              

                                             Figure 3. Structure of tooth

4)PERIPICAL:
This technique focus on two complete teeth from root to crown. See (fig 4) 

                                              

                                        Figure
4. Structure of tooth

 

 4. Dental Photograph

 

  Dental
Photograph See (fig 5) is an image which is taken with the help of camera. In
some case where dental radiograph is not obtained easily on that case we use
Dental Photograph. It is easy way to collect Dental Photograph where we can
collect Dental photograph of various persons. For identification of human
Dental photograph also play an important role. Use of dental Radiograph in
identification of human takes less cost and it is easily Available. We can use
any camera but its resolution is good enough so that it can take good quality
of image.Use of good quality of dental photograph gives better output and make
our Dental based identification system more effective. In below figure we see
the Dental image of various persons.   

 

                                     Figure 5. Structure
of tooth

 

 

   5. Literature Review

 

    In this review we present all the previous
review of some selected paper in the form of table. Below  table illustrates the literature review of
various techniques which is used by different authors in Previous Years.

                                       Table 1. review of various techniques

Year

Reference

Enhancement
Technique

Segmentation Technique

Feature
Extractor

Matching
Technique

Results

2017

G. Jaffino, A.Banumati, Ulaganathen Gurunathan, J.Prabin Jose 6

Butterworth High pass filter

Bite viewing radiograph using Spline Isolation, Missing tooth
detection

Moments Feature Extraction

K-NN classification & Texture based, Fuzzy classification based
matching

Efficient Algorithm with 93% accuracy

2015

Soma Datta & Nabendu Chaki 7

De noising winner filter

Watershed & snake Algorithm used

ROI Extraction such as volume, size, area
 

NA

Efficient but not 100% accurate

2015

Dipali Rindhe & Ganesh Sable 9

Assumed good quality images were used in JPEG format

Thresholding

SIFT ALGORITHM

Matching feature based on Euclidean distance

It give better matching rate for identification

2014

Vijaya  8 Kumari pushparaj,
Ulaganathen Gurunathan, Banumati Arumugan

Use good quality of radiograph & photograph

Missing tooth Identification & Spline isolation

Contour Extraction

Binary (SVM) Contour Based Matching

This Method Outperforms other methods in terms of Computation time
& hit rate
 

2012

Shubhangi C.Dighe & Revti Shriram3

Histogram equalization

Extraction of ROI

Thresholding

Difference between radiograph based on 
dental work , mode, median, skewness
 
Control Point Selection of  tooth
contour
 
 
 
 

Method give direct visualization of matching or not matching &
unsatisfactory for two blurred image

 

 

                             

                                     Table
1.
review of various techniques cont

Year

Reference

Enhancement
Technique

Segmentation Technique

Feature Extractor

Matching
Technique

Results

2011

C.K Modi 1017

Assumed good quality of images
were used
 

Radiograph Segmentation

Fourier Descriptors

Absolute and Euclidean
distance

66.667 % Precision

2009

P.L.Lin & Y.H.Lai 1117

Hommorphic Filtering ;
Adaptive contrast stretching morphological transformations
 

Thresholding ; Horizontal
& Vertical integral projection

Relative length/width radio
of a teeth, Relative crown size

Only classification is
performed

94.9% for molars &95.6%
for premolars.

2008

S.Kiattisin 1217

Brightness Adjustment ;
Binary image conversion

Chain code Decoding

Special features of teeth

Absolute matching between
decoding & statistical code
 

Same code match=90%(Same
pattern); 50%(different pattern).

2006

O. Nomir and M. Mottaleb 1317

Binary image masking

Radiograph Segmentation:
Iterative & Adaptive thresholding ; Horizontal & Vertical integral
projection
 
 

Tooth Contour

Hierarchical Chamfer
Matching Algorithm

Out of 50PM quer images,
Rank I-40, Rank II-3, Rank III-2, Rank V-4, Rank VII-1 images.

2004

O. Nomir and M. Mottaleb 1517

Binary Image Masking

Iterative & Adaptive
Thresholding : Horizontal
& Vertical integral projection
 
 

Signature vector From tooth
contour

Absolute distance matching

Out of 29 PM query images,
Rank I-21, 4 out of %PM images correctly retrieved.

2004

Anil K. Jain 1417

Assumed good quality images
were used

Horizontal & Vertical
integral Projection

Contour of Teeth &
Shapes of Dental work

Computation of image
distances matching

Out of 11 PM query
images,Rank-I-72%, Rank-IV-91%, Rank-VII-100%
 

 

 

 

 

6. Proposed Methodology

 

     The methods we have proposed here
comprises  five main processing steps.
All the image will pass these process. First dental radiograph is sent in to
image enhancement technique where we improve the quality of image then image is
sent to pre-processing stage where we process image then image is segmented in
segmentation process then we extract some special feature by use of Feature
Extractor then we match the image to get desired output.

The proposed system is
implemented with five modules:

1.
Pre-processing

2. Image
Enhancement

3. Segmentation

4. Feature
Extraction

5. Dental image
Matching

 

Block
diagram of proposed system

The block diagram of
dental biometrics is shown in Figure 4.1.

 

Figure 4.1: Block diagram of Dental
biometric system

Pre-processing

Feature Extractor

Matching of dental image

Output of image

Image Enhancement

Segmentation

Dental radiograph

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 6.1. Pre-processing

    It is the first step or fundamental
step of Digital image processing. Image pre-processing or Image Acquisition
basically deals with improving the quality of image. If our image quality is
poor then we have to remove noise from that image and make our input image more
accurate. For removing Noise various types of Filters is used.

Removal
of Noise in done in 3 ways:

 1. Remove Noise by Linear
Filtering.

 2. Remove Noise Using
an Averaging Filter and a Median Filter.

 3. Remove Noise By Adaptive Filtering.

 

 

6.2. Pre processing

  It is Simplest and mostly applied in various
areas of digital image processing. It is used in those areas where the
subjective quality of images is important for human perception. The idea behind
this is to highlight certain features of interest in an image.

6.3.
Segmentation

  In
Segmentation process we partition an image into constituent parts or object. In
this we segment our dental photograph or radiograph such that each region
contains only a single toot.  There are many different ways to perform image segmentation, including:

1. Thresholding Methods such as Ostu’s method.

2. Transform Methods such as watershed segmentation.

3. Texture Methods such as Texture Filters.

6.4. Feature Extraction

  Feature Extraction is a type of Dimensionally
reduction that efficiently represents interesting parts of an image as a
feature vector. This is technique is used when image size are large and reduced
feature representation is required to complete tasks such as image matching. In
this step we extract useful features of teeth so that it helps in matching and
classification.

6.5.
Matching

  After doing all the previous process such as
pre-processing, image enhancement, segmentation, feature extraction the last
step is to complete our target is matching of image. For matching we have to
develop an algorithm based on properties applied and image features and
developed distance matching. Accurate matching leads good identification which
is our desired goal.

7. Expected Results

  We expect that our
Dental Biometric system is able to Identify Person Based on their Dental
records. We use various Techniques and Methodology in our system so that it can
identify person more precisely and accurately. In previous system of Dental
Biometrics for Human identification Various Technique is used so our task is to
use previous methods and Techniques and adding new Techniques to make our
system more Effective.

8. Conclusion and Future work

  Dental
biometrics is not only used for identification of person but it is act as a
confirmatory tool. It is used in forensic identification of human as well as
disaster victim classification. Among other Biometric Methods for Identifying
Human, Dental based Identification (DENTAL BIOMETRIC) gives better results in
various conditions where person body parts were Damage. With the help of above
research in this area, we can make an effective Dental Biometric System with
efficient and time saving methods with accurate Results. Our main Challenge and
Future work in Dental Biometric system for human Identification is to deal with
poor quality of images, Teeth overlap, teeth shape change consideration due to
ageing.

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