Benefits to the business and medical sectors through application of geometric convexity-based methods to image and data processing
Submitting Institution
Swansea UniversityUnit of Assessment
Mathematical SciencesSummary Impact Type
TechnologicalResearch Subject Area(s)
Mathematical Sciences: Pure Mathematics, Applied Mathematics
Information and Computing Sciences: Artificial Intelligence and Image Processing
Summary of the impact
Researchers in the Department of Mathematics at Swansea University have
developed novel
geometric methods for image processing, feature extraction and shape
interrogation. The research
has delivered commercial and clinical impact in a variety of settings,
ranging from new water
marking techniques to improve piracy detection in the film industry, to
medical research
investigating the replacement of traditional CT scans with safer MR scans.
The research has also
delivered an automatic feature and gap detection tool that has been
successfully applied to aircraft
data files provided by BAE Systems. A consultancy company is exploiting
the methods and a
licence for the commercialisation of the technology is in process.
Underpinning research
The research underpinning this impact case is based on compensated
convexity theory, a powerful
mathematical tool discovered by Kewei Zhang (Professor of Mathematics at
Swansea University
until December 2012), which introduces a new class of geometric
convexity-based transforms.
The initial paper on this work, that provides the foundation for all later
developments, was
published in a highly-regarded pure mathematics journal in 2008 [R1].
Compensated convexity theory provides a geometric convexity-based
tight-approximation method
for general functions [R1, R2]. This can be used, in particular, as a new
way to identify singularities
in functions, and thus can be exploited, via a numerical implementation of
the transforms, to detect
features in images or data or remove noise from images.
Based on this insight, innovative geometric methods for image processing,
feature extraction and
geometric interrogation have subsequently been developed [R3-R6]. Key
advantages of this new
geometric approach over previous image and data processing techniques
include its use of blind
global methods which are stable under perturbation and different sampling
techniques, and also
provide scales for features that allow users to select which size of
feature they wish to detect.
Applications for the numerical implementation of the new convexity-based
tight-approximation
methods to perform specific image and data processing and feature
extraction tasks have been
developed in collaboration with organisations such as BAE Systems, the
John Radcliffe Hospital,
Oxford, and Fortium Technologies since late 2008 onwards. The research has
been conducted in
conjunction with parallel work in the theory of geometric singularity
extraction.
Applications include image processing, reconstruction based on scattered
data such as impulse
noise removal, image repair, affine ridge, valley and edge detections,
corner detection, sharp
turning point and intersection detection for lower dimensional objects,
end point and boundary
detections for manifolds and curves, multiscale medial axis, boundary
detection of objects based
on scattered samples, high oscillation area detection, outlier enhancement
and suppression, and
geometric watermarking.
Following the initial work of Zhang, the further development of the
theory, its applications to image
and data processing, and the associated numerical methods and software,
has been carried out by
a research group consisting of Professor Kewei Zhang, Dr Elaine Crooks
(Associate Professor in
Mathematics, Swansea University) and Dr Antonio Orlando (Lecturer
in Engineering at Swansea
University until September 2010), between late 2008 and the present. Two
short-term research
assistants (Dr Yasmin Friedmann, March-June 2012, July-August 2013,
and Ms Natalia Ubilla,
May-June 2012) were also employed by Swansea University to assist with
this project.
Two substantial research papers on the theoretical aspects of geometric
singularity extraction have
been submitted for publication [R3, R4] and further research papers are in
preparation; these
papers collectively develop the theoretical framework that underpins all
of our applications to
image and data processing and feature extraction tasks. A UK patent
application on these new
methods of image and data processing (GB 0921863.7) was filed by Swansea
University, with
inventors Zhang, Crooks and Orlando, in December 2009, and a PCT (Patent
Corporation Treaty)
application (WO 55010) was filed in December 2010 [R5]. The inventors
entered the UK national
phase of the patent application process in June 2012.
References to the research
Publications and submitted articles (R1, R2 and R5 best show the quality
of the research):
R1) Kewei Zhang, Compensated convexity and its applications, Ann.
Instit. H. Poincare
Analyse Non-Lineaire 25 (2008) 743-771
R2) Kewei Zhang, Convex analysis based smooth approximations of
maximum functions and
squared-distance functions. J. Nonlinear and Convex Analysis, 9 (2008)
379-406
R3) Kewei Zhang, Antonio Orlando and Elaine Crooks, Compensated
Convexity and
Geometric Singularity Extraction Part I — Basic Ridge, Valley and Edge
Transforms. (56
pages; submitted to Math. Models Methods Appl. Sci.)
R4) Kewei Zhang, Antonio Orlando and Elaine Crooks, Compensated
Convexity and
Geometric Singularity Extractions Part II — Hausdorff Stable Ridge and
Exterior Corner
Transforms. (35 pages; submitted to Math. Models Methods Appl. Sci.)
R5) Patent application: Image Processing and Feature Extraction — UK
patent application ((GB
0921863.7) December 2009, PCT (Patent Corporation Treaty) application (WO
55010)
December 2010. Application for the UK National Phase, June 2012.
Grant awarded: EPSRC `Pathways to Impact' grant (£25,070 — Development of
tools in image
processing, feature extraction, approximation and interpolation, and shape
interrogations in
computer aided geometric design), awarded to Kewei Zhang via the College
of Science Research
Committee, Swansea University, which funded the employment of two research
assistants in the
period March-June 2012 to develop a user interface and webpage to aid
demonstration of the
image processing software to industry, etc. This work was important in
underpinning impact d).
Following the initial identification of the potential impact of this
research in late 2008/early 2009, the
Swansea University Department of Research and Innovation funded the patent
and PCT
applications (2009 and 2010, respectively), the Wales Institute of
Mathematical and Computational
Sciences (WIMCS) and the Department of Mathematics, Swansea University,
allowed Kewei
Zhang and Elaine Crooks to spend time developing the theory and numerical
methods for
applications, and the Department of Mathematics also provided computing
equipment and
software.
Details of the impact
The case described here centres on the impact of our new technology on
the business sector.
a) Improving piracy detection for the film industry [C1]
The geometric techniques developed at Swansea are being used as a tool
for inserting robust
watermarks in individual frames of a film in order to improve piracy
detection in the film industry.
Fortium Technologies Ltd were impressed by a test example of using the
technique to embed a
text-based watermark in an X-ray. Piracy is a major commercial problem for
film companies,
costing the US economy alone over $20 billion per year#, and
there are currently only a couple of
companies worldwide involved with film watermarking. There is thus a
strong interest within the film
industry to find alternative approaches; Fortium is seeking to develop a
method of embedding a
watermark in each frame of a film so that, if the film is pirated,
information about when or where the
piracy took place can be obtained.
Zhang, Crooks and Orlando have subsequently entered into a formal
contract with Fortium to
develop their geometric method to meet the specific needs of film
watermarking. Trials of
embedding a watermark into a test image provided by Fortium have shown
that our approach
allows embedding of a watermark in a localised way that gives a high PSNR
(peak signal to noise
ratio) that is well above the threshold that the industry accepts as being
enough to ensure the
watermark will be imperceptible to the viewer: the PSNR for our locally
embedded watermark is
66dB and the industry threshold is around 45dB. Our technique allows
watermarks that are either
image or text based, and can be incorporated anywhere within the image
frame, both of which are
seen as key advantages in comparison with existing watermarking
techniques. The inclusion of
text-based watermarks allows the possibility of human-readable watermarks.
Current development
is focussing on trying to improve the robustness of our watermarking
approach.
"...the project has already enough promise to get some of the biggest
content owners and
producers in the movie and television industry eager to monitor its
progress"
(Fortium CEO)
b) Feature and gap detection for computer aided design [C2, C5]
Working with BAE Systems, the Department has provided a confidential
report concerning the
extraction of intersection and high curvature parts and gaps for
geometrical objects based only on
given loosely sampled point clouds defining the surfaces of the object.
Following a visit of Zhang
and Crooks to BAE Systems Advanced Technology Centre in Bristol in June
2011, including a
well-received presentation on some of our new methods and subsequent
discussions, we were
provided with some data files of surface meshes for the surfaces of
aircraft, to which our
intersection/high curvature and gap detection methods were successfully
applied.
One application of our gap-detection method is as an automatic tool to
find gaps between parts of
the underlying geometric design of an aircraft, for instance in data files
provided by manufacturers
to engineers for the purpose of performing fluid-dynamics simulations.
These gaps are deliberately
left for soldering purposes, whereas for fluid dynamics simulations,
different parts must be
connected. Currently such gaps are detected by a time-consuming manual
process, while our
methods provide a fast, automatic gap-detection tool. Work is ongoing in
the field of application.
c) Quantitative comparison for medical images [C3, C6]
A further confidential report was provided in June 2012 to clinicians
from the John Radcliffe
Hospital, Oxford, who are investigating the feasibility of replacing
traditional, benchmark
computerised tomography (CT) scans of children's skulls, known to be
accurate but also to impart
high levels of radiation, by safer magnetic resonance (MR) scans. The
report was concerned with
quantitative Hausdorff-distance measurement between image sets based on
magnetic resonance
(MR) and computerised tomography (CT) scans of a phantom box, with the aim
of providing a
quantitative method of comparing CR and MR scans.
d) Commercial potential identified by consulting company [C4]
After a demonstration in January 2013 of a selection of our image
processing and feature
extraction methods using the interface initially developed with the EPSRC
`Pathways to impact'
grant described above, the consulting company Cadarn Technik, which has
extensive experience
of dealing with video algorithms and of interacting with electronics,
chemical, materials, and life
science companies, expressed an interest in commercialising our
technology. A draft of a licence
for the purpose of commercialisation of this technology is in process.
# http://www.theguardian.com/film/2012/may/11/release-date-piracy-time-warner
Sources to corroborate the impact
External contacts:
[C1] CEO, Fortium Technologies Ltd
[C2] Communications, Networks & Image Analysis, BAE Systems
[C3] Nuffield Department of Surgical Sciences, University of Oxford, and
Department of
Maxillofacial Surgery, John Radcliffe Hospital, Oxford
[C4] Director, Cadarn Technik Ltd, Dylan Thomas Centre, Swansea, SA1 1RR
Confidential reports to external bodies:
[C5] `Shape Interrogation of Some BAE Systems Geometric Models', provided
to BAE Systems
Advanced Technology Centre (October 2011)
[C6] `A Comparison of 3D Reconstruction from MR and CT Scans of a phantom
Box', provided to
Nuffield Department of Surgical Sciences, University of Oxford, and
Department of Maxillofacial
Surgery, John Radcliffe Hospital, Oxford (June 2012)