GIS as a Tool for Facial Recognition
Vikas Lachhwani
Eok Kim
Abstract
GIS has proven capabilities for spatial database management and analysis.1 However, the
application of GIS is usually limited as a “Geographic” Information System. This narrowness is
reflected in the gamut of applications that use GIS as well as the functions available in the
popular GIS software. This paper is an attempt to demonstrate that these capabilities can well be
extended beyond the limited domain it is usually applied to. It aims at emphasizing that GIS can
be utilized as a “Spatial” Information System. Facial Recognition (FR) for surveillance has been
in existence for the past few years. Different FR systems employ different techniques, methods
and procedures. It does not try to challenge the existing FR systems on the methodology used or
the procedures involved. Rather, it proposes that GIS as a well developed technology, can
augment technologies that work with spatial databases. This paper tries to demonstrate that GIS
can be effectively used for implementing such a system and tries to list the benefits of using GIS
for such a system. It employs a multi disciplinary approach utilizing knowledge of GIS,
computer programming and 3D modeling. The software used for this exercise were AutoCad,
ArcGIS and Microsoft Visual Studio (Visual Basic 6).
Facial Recognition Systems
Facial recognition technology is hardware and software that allows computers to identify people
by their faces. It is a subset of biometrics, other examples of which include fingerprint scans,
retinal scans, and voice identification. Facial Recognition (FR) Systems have been in existence
for past few years. They have been implemented in conjunction with other identification systems
1
Harnessing the Power of GIS for Energy Industries , [Website of ArcUser Magazine], [Online]. Available:
http://www.esri.com/news/arcuser/1099/umbrella8.html. [September 30, 1999].
* ArcGIS, ArcIMS, ArcObjects, MapObjects are trademarks, registered trademarks, or service marks of ESRI in the
United States, the European Community, or certain other jurisdictions.
for surveillance in places that need high security and monitoring. Different FR systems employ
different techniques, methods and procedures. However, the common process across all FR
systems is that they use unique characteristics in a human face and create and utilize a parent
database to identify a test case from. The systems map the facial characteristics and store them in
a parent database. For identification, the system maps the facial characteristics of a
person/suspect and finds the best match from the database.
Using GIS
The above discussion on FR systems explains that FR systems are based on mapping the facial
characteristics and developing a database. Mapping a human face generates spatial data and the
data must be stored in a database for future reference. GIS has proven capabilities for spatial
database management. GIS software is inexpensive compared to the cost for developing entirely
new software for a specific task. It can be PC or a Client/Server system and can be easily
integrated with other systems. It requires small records with fewer data in each record. The most
important benefit of using GIS is that it shifts the challenge from database management to
database analysis.
Concepts
Biometrics
Biometrics are automated methods of recognizing a person based on a physiological or
behavioral characteristic. Among the features measured are: face, fingerprints, hand
geometry, handwriting, iris, retinal, vein, and voice. Biometric technologies are
becoming the foundation of an extensive array of highly secure identification and
personal verification solutions.2
2
Introduction to Biometrics, [website of the Biometrics consortium], [Online]. Available:
http://www.biometrics.org/html/introduction.html [May 15, 2004].
Methodology: Mapping
Every face has unique dimensions and these dimensions are marked by key identification
points. For example, the height of ones ear or the distance between ones eyes is fixed; the
points identifying these distances are the key identification points. The authors used
Geometric Mapping for mapping the facial characteristics. In this procedure, facial
geometryis traced after the key identification points are located. Existing FR software map up
to 22 identification points. For simplifying the process and fit the project into the time frame,
this project mapped 10 identification points for each face. The points were chosen based on
the uniqueness of their location such as the tip of the nose, the top and the bottom of the ear
and so on.Mapping was done with the help of AutoCad, creating a .dxf file. The CAD files
were then transferred to ArcGIS and Geodatabase and shape file were created.
Geometric Mapping
Figure 1 and 2: Locating identification points. Figure 3: geometric mapping
figure 4:transferring the data into ArcGIS
Data Creation
After the CAD files were introduced into ArcGIS, the x-y coordinates of the identification points
were calculated with the help of a small code provided by ESRI with ArcGIS. The relative
dimensions of the components of distances are identified and the angle between the points is
calculated. For simplifying the project, only a rotation along x-axis (forward or backward tilt)
was considered. We considered only the relative dimensions of y-components of distances and
one angle. The data developed was stored as the key characteristics of an individual.
Figure 5: Relative dimensions of components
Data Analysis
The raw data was converted into a format more conducive for conducting database search.
X_coordinate
Y_coordinate
point_id
15190.1041380293 162.577139855654 3
…
…
…
Raw Data
Person
1
10
Point
2
1
1
Distance
2
Angle
1
Ratio
1
Figure 6: The converted data
A Visual Basic program was written to search test cases for individuals with existing records
in the database. The first step to locate a person in the database is to find the best match in
terms of angle range. The data where the angle falls within a particular range of the test case
(angle≥-α AND angle≤+α, where α is an angle value of selected data to find match) are
selected. The results of the search are saved into the database. In the second step, the best
match in terms of ratios is identified (ratio≥-α AND ratio≤+α, where α is a ratio value of
selected data to find match). The intersection of the two results is identified and the
proximity of parameters to the test cases is scored. The best match is found based on these
scores.
Test
Image
Output image
from the
database
Figure 7: Results: The program developed for analysis
Discussion
The project was executed with limited knowledge of biometrics and limited time to develop an
extensive algorithm needed for the exercise. The experiment showed that GIS systems can well
be used for spatial analysis well beyond the geographic domain.
Availability of expertise on biometrics and development of an extensive algorithm would help in
developing the concept proposed by the authors. Introducing more complexities into the
algorithm would help in refining the search to a great extent.
Further Scope for GIS
GIS systems can be used to integrate the operations that were conducted in this project to
develop an integrated package for developing and analyzing databases. This can be done with the
help of packages like ArcObjects and MapObjects. A user interface can be developed that allows
location of identification points eliminating the need for CAD software. The system can be
developed on multiple tiers and can be put online with the help of software like ArcIMS for
people to check the criminal records of potential employees or renters. The technology for
developing such a system exists and all it needs is multi-disciplinary expertise and patronage.