UWE Bristol Engineering showcase 2015

Christopher Ovaletor
Meng Mechanical Engineering
Introduction
There is a need to detect the lens of hidden cameras in order to eliminate
piracy. One of the main problems is that of false positives, i.e. mistaking shiny
objects within a busy scene for cameras. No method has yet been determined
that deals with the issue of false positives and this project will involve
extensive research into these application areas. Experimental work aimed at
developing and testing a robust method for lens detection in a busy
environment with emphasis on been able to distinguish between the lenses
of a video camera and other objects will be undertaken. Research consisted of
understanding the problems they pose, review and examination of current
systems and/or machines been used to combat these problems. Experiments
were conducted under controlled conditions and the images captured were
analyzed for patterns and particle composition. An algorithm was created
aimed at effectively distinguishing between video camera lenses and other
test objects.
Number of objects
500
450
400
350
300
250
200
150
100
50
0
Number of detected objects
Hidden lens and camera detection
Experiments
In order to perform an initial analysis experiments were carried out on a
wide variety of test objects that could be present in a setting where
identification of hidden camera lenses was required. Measurements were
made and the setting was kept controlled at all times. Both static and
dynamic experiments were carried out. The dynamic experiments were
carried out by marking 5 set positions on a straight line and moving the
torchlight from left to right along the line.
Analysis
Both the static and dynamic experiments were a success. Analysis was
carried out on the cropped images using NI Vision Builder (NIVB). NIVB
interprets images mathematically. Parameters that were of direct relevance
to the project i.e. suitable for particle analysis were used to create an
algorithm for processing the images and the results were collated on excel
and analysed. Significant patterns and value differentials were detected. The
parameters that provided the best ways of eliminating false positives were
noted.
Project Supervisor
Dr Melvyn Smith
Project summary
The aim of this project was to find an effective way to
detect video camera lenses in a cinema setting with
primary focus on been able to distinguish between
the video camera and other shiny objects which can
give false positives. Research and investigative work
was carried out and results analysed to determine
the possible parameters of image analysis that could
be viable solutions.
Project Objectives
1. Research of optical principles like linearity,
reflection and spectral reflection.
2. Research of previous work done related to the
project.
3. Investigation into the methods which can be used to
detect hidden cameras or bugs.
4. Image processing techniques will be investigated.
5. Static and dynamic experiments will be carried out
to fully ascertain the difference in reflection patterns.
6. Tests will be carried out on images to identify
patterns and conduct particle analysis. Results will be
collated and analysed using excel.
7. Experimental work in various settings will be carried
out to test new or improved methods using vision
equipment and software.
8. An algorithm supported by experimental results will
be proposed aimed at distinguishing between the
video camera lens and other objects.
9. Areas of improvement and further work will be
stated.
Project Conclusion
1. The reasoning behind the project was fully
identified. The issue of false positives was noted as the
area of utmost focus .
2. Some of the recent inventions in the field were
assessed in detail.
3. A thorough knowledge of the use of equipment’s
was attained as well as a working knowledge of the
NIVB software.
4. All experiments were carried out under controlled
conditions and conducted successfully. Image analysis
produced significant results.
5. An algorithm was created that worked perfectly for
all the images captured successfully identifying only
the video camera lens in all cases both static and
dynamic.