Mobile Application for Ulcer Detection
temperature is set to room temperature and
the light is set to a very dim environment. A
cold background behind and underneath the
object is mandatory. The background may
be a concrete wall or a cold towel, and the
object can be placed on a surface where the
temperatures from the object and from the
surface have minimal heat transference. If the
image is to be captured by a single user, a
non-reflective material such as velvet can be
placed around the leg as it can act as a cold
surface (background). This simple DIY (Do It
Yourself) can be done at home. The distance
between the object and the camera must be at
least 12 to 16 cm. In addition, there should be
no hot objects in the background such as an
electrical switch, current carrying wire, hot
food, computer, etc. Acquiring a clean image is
of utmost importance.
The ulcer was simulated by heating a small
metallic object (coin) and pressing it against
the foot for heat transference. The heat
transference was carefully monitored. The
temperature difference on the foot was
carefully monitored to have a region of 2.2
degree Celsius temperature difference. The
thermal image is captured when the desired
temperature difference is achieved.
The smartphone standalone application
requires loading the thermal image from the
phone’s gallery. The FLIR ONE app provides
thermal readings with an accuracy around 0.1
degree Celsius.
2.2. Image Processing
A standalone smartphone system with image
processing capabilities is made possible
with OpenCV and FLIR ONE SDK. OpenCV
is a computer vision library used for simple
computer vision and image processing
techniques on various platforms [25] . It is
recommended to use an older version for
better support and documentation. OpenCV
module was imported and linked to the
Android application. The Integrated
Development Environment (IDE) used for
Android programming was Android Studio.
Although there were many other well-known
IDEs, Android Studio was selected, as it is
Java based and easy to use.
Fig. (1) illustrates the complete image
acquisition and image processing steps
in detail. The acquired thermal image
consists of a normal color image as well as
the radiometric data embedded within it.
There are two sides of the obtained thermal
image: the blended MSX image, which is an
RGBA image, and the Thermal Radiometric
Kelvin, which provides the required thermal
radiometric data. The radiometric data is
extracted from the thermal image. FLIR
provides this support for developers who
use FLIR ONE products. FLIR ONE SDK
was used to access the radiometric data
embedded within the thermal image. FLIR
ONE SDK features were invoked to access the
radiometric data. The path of the acquired
image in the gallery was passed to the SDK
and the radiometric data were obtained.
The radiometric data is in the format known
as Little Endian. Hence, a one-dimensional
(1D) data was acquired for the thermal
image. The 1D data was converted to 2D
data to perform computer vision and image
processing techniques to acquire accurate
results. The number of values or pixels held
by the radiometric data is 320 (Rows) times
240 (Columns), which is 76,800 data values.
However, the data was scaled to get a matrix
Current Pedorthics | January/February 2020
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