Image Processing and Mixed Reality
The Image Processing and Mixed Reality group at Birmingham City University consists of research staff and academic members from the School of Computing and Digital Technology.
The group researches a range of new and exciting applications for analysing and processing still image and video data, and is linked directly to a wide variety of application domains. These include medical image analysis systems, video and image distribution systems, low-level image assessment, image feature classification, real-time video processing, 3D modelling and 3D processing, live television studios and real-time video processing systems.
Our current research is driven by industrial applications and has clear links to medical diagnosis, simulation and treatment, TV and video production, and the automotive and manufacturing industries. All the research within this group is focused on using a range of scientific and mathematical techniques and draws on a strong emphasis in Digital Signal Processing (DSP). We currently have exciting opportunities in all of these fields for new students wishing to pursue MPhil and PhD study within our group.
Segmentation of teeth structures from Computed Tomography CT and Magnetic Resonance (MRI) images
This research is being carried out jointly with Birmingham City University’s Faculty of Health and the King’s College, London School of Dentistry. It is focusing on creating automated segmentation techniques to provide accurate 3D models of human teeth. These tooth models are then used within haptical dental training systems to provide a flexible simulation and learning environment for dental training.
3D surface segmentation of Computed Tomography (CT) Images
This work is linked with the School of Health and Social Care at Birmingham City University and is focused on improving the segmentation of soft tissue within CT images through statistical model analysis and classification.
Problems associated with the accurate segmentation of CT data are being analysed and new methods of guided segmentation are being developed. This will aim to improve both the accuracy of medical segmentation software and procedure planning systems.
Objective performance evaluation of edge and surface detection methods
This work is looking at new methods for objectively assessing the performance of low-level edge detection algorithms. Fully quantitative measures have been developed which assess the similarity between target images alongside the accuracy of both edge and surface detection results. These methods can be applied to any edge and surface detection algorithms and provide a clear objective analysis of their accuracy.
2D and 3D edge detection using statistical features
This research is looking into the improvements offered to edge segmentation in images through the use of statistical features. New methods of 2D and 3D edge detection are in the development and the results of these techniques show improvements in textured and noisy image data where many traditional techniques fail.
Illumination and colour coherence in video compositing
This research is looking into new methods for automatically calculating measures of illumination and colour within video frames for automated compositing systems. Calculating automated global measures of luminance and colour realism within composited scenes allow us to optimise the compositing of natural scenes when applied within automated compositing systems.
Onset pre-visualisation in film production
This research is looking into new methods for providing real-time on set actor pre-visualisation and feedback for the film industry. This concept of pre-visualisation can be applied to an actor in real-time attempting to interact with a virtual character. The aim of this work is to allow film crew to see instant results of any interaction and adapt their production as they desire. Currently methods are being evaluated to improve the level of real-time information presented and the accuracy of the interaction.
Real-time interaction in virtual TV studios
This research is looking into the methods of providing interaction between actors and virtual objects within a live virtual TV set. Automated methods of calculating depth within the virtual TV studio are being researched and new real-time occlusion systems have been developed.
The group have a testbed for assessing the interaction and have developed a framework for measuring the level of interaction accuracy.
Prof Cham Athwal - Associate Head of School (Research)
Cham is a Professor of Digital Technology and Head of Research within the DMT school. His research interests cover 3D modelling, image processing, video processing, digital signal processing web technologies and simulation. Currently Cham is supervising eight PhD/MPhil projects covering a range of subjects including digital audio processing, digital image processing and virtual environments. Email: email@example.com Phone: +44 (0)121 331 5458
Dr Ian Williams
Ian is a Senior Lecturer and Subject leader in Image and Video technology within the school of DMT. His research interests are in low-level image processing, feature extraction and image filtering. Ian currently supervises PhD students in both the image, video and signal processing fields. Email: firstname.lastname@example.org Phone: +44 (0)121 331 7416
Jerry is a senior Lecturer and Subject Leader in Digital Media Technology within the DMT school. His research interests include interactive and personalised media on commercial platforms, involving agent-based brokerage; media distribution architectures and virtual environments applied to environmental construction; learning environments; simulations; spatial interactions and communication in virtual worlds. Email: email@example.com Phone: +44 (0)121 331 7416
Dr Münevver Köküer
Münevver is a Research Fellow within the DMT school. Her research interests cover speech and audio pattern processing, data analytics, pattern recognition, machine learning and image processing. Münevver is currently carrying out research on her specialist areas, developing new research projects and grant applications, developing collaborations and partnerships as well as disseminating research. She supervises PhD projects on digital audio processing, digital image processing and virtual environments. Email: firstname.lastname@example.org Phone: +44 0121 331 7410
Matt is a Senior Lecturer and Programme leader in Image and Video technology within the school of DMT. His current research interests are focused on providing new methods for pre-visualisation or virtual elements within film production. Email: email@example.com Phone: +44 (0)121 331 7443
Gregory is working towards his PhD within the DMT school and researching the development of novel methods for aiding in real-time visualisation and interaction for actors in live television environments. Email: firstname.lastname@example.org Phone: +44 (0)121 331 7416
Alan is currently working towards his PhD alongside being a visiting lecturer within the DMT school. He's research interests include automated compositing in video and video scene estimation using algorithmic processes, for automated colour coherence, variance analysis in scene illumination and improved match moving. Email: email@example.com Phone: +44 (0)121 331 7416
Sam is currently researching for his PhD and undergoing image processing research which is looking to classify textures in soft tissue, as well as applying 2D and 3D statistical based boundary detection algorithms to biomedical computed tomography and magnetic resonance images, for the purpose of segmenting tumours in soft tissue. Email: firstname.lastname@example.org Phone: +44 (0)121 331 7416
Muadh Al Kalbani
Muadh is currently researching towards his PhD in image and video processing. His area of research involves the development of new solutions to real-time mixed reality systems and he is currently looking to improve the interaction possibilities between humans and virtual scenes using depth and video features.
Email: Muadh.AlKalbani@mail.bcu.ac.uk Phone: +44 (0)121 331 7416
We have many emerging areas of research in both image and video technology which are available for postgraduate study towards MPhil and PhD awards. In conjunction with projects listed above the following opportunities are always available. For more information on any of these topics please contact Prof Cham Athwal or Dr Ian Williams.
- Medical image processing
- Image segmentation, filtering, analysis and classification of soft tissue.
- Guided segmentation between MRI and CT images.
- Real-time CT processing for virtual model replication.
- Video processing
- Actor interaction with virtual elements of video.
- Real-time analysis of scene conditions.
- Automated object compositing in broadcast video.
- Guided 3D reconstruction.
- Dynamic 3D model creation from CT images.
- Improving segmentation for 3D model creation.
- Video over networks – KTP Industrial project with Gas St Works Ltd
- Shape classification within cold rolled steel sections.
- Tracking of objects in video for automotive applications
- Synchronisation of multiple media streams, including video and discrete data
There are a range of resources, code files and applications available upon request. For any access to these files or programmes please contact Dr Ian Williams.
3D Surface Detection Models: A model for offering improved 3D surface detection in slice CT and MRI data.
Statistical edge detection techniques: A series of algorithms are the product of the thesis titled “Edge Detection of Textured Images Using Multiple Scales and Statistics”. They apply several two-sample tests to 2D image data to locate edge information.
Multiple Scale Edge Detectors using ANNs: The algorithms presented in these files extend the 2D edge detectors with the use of Artificial Neural Networks (ANN). The ANN application allows both the training and classification of edges of varying scales within an image, using a variety of statistical tests. These algorithms can be trained around a specific application and therefore tailored to a given type of data.
Edge and Surface Performance Measures: A series of both 2D and 3D performance measures for assessing the quality of edge and surface detection methods.
For more information on these resources, contact Dr Ian Williams.
Hough, G., Williams, I., Athwal, C. Measurements of Live Actor Motion in Mixed Reality Interaction. IEEE International Symposium on Mixed and Augmented Reality. Munich, Germany. 2014.
Hough, G., Williams, I., Athwal, C. Measurement of Perceptual Tolerance for Inconsistencies within Mixed Reality Scenes. IEEE International Symposium on Mixed and Augmented Reality. Munich, Germany. 2014.
Williams I, Bowring N, Svoboda D, A Performance Evaluation of Statistical Tests for Edge Detection in Textured Images, Computer Vision and Image Understanding.
Barbosa, I.B. , Theoharis, T. , Schellewald, C. , Athwal, C., ‘Transient biometrics using finger nails’, IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2013, Arlington, VA.
Hough G, Athwal C and Williams I. Advanced Occlusion Handling for Virtual Studios. Lecture Notes in Computer Science, Springer 2012.
Hough G, Athwal C and Williams I. 'ScaMP: A Head Guided Projection System' ACM Designing Interactive Systems'12. Newcastle, UK. 2012
Williams I, Athwal C and Foss J. Developing Real-time Virtual Environments from Video Data.IET Seminar on Video Data Analysis, IET, London 2011
Williams I, Shirvani B and Mourier JM. Measurement of Cold Rolled Steel Sections Using Digital Image Processing. Journal of Key Engineering Materials, vol 473. Trans Tech Publications, 2011
I. Williams, D. Svoboda and N. Bowring, “A Novel Performance Metric for Grey-Scale Edge Detection” – International Conference on Computer Vision Theory and Applications 2010
J. D. Foss, B. Malheiro, “Media Component Brokerage”; Proceedings of the Fourth European Conference on the Use of Modern Information and Communication Technologies – ECUMICT 2010, Gent, Belgium, March 2010
Elson, B., Athwal C., Reynolds P., “Creating the World of Augmented Dental Training”, E-Learn 2009, World Conference on E-Learning in Corporate, Government and Healthcare, AACE Vancouver, 2009
I. Williams, “Edge Detection of Textured Images Using Multiple Scales and Statistics”. PhD thesis, 2008
N. Bowring, I. Williams, C. Johnson and J. Jaiswal, “Fatigue Crack, Squat and Wheel Burn Detection by a Multi-Scale Statistical Image Processing Technique”; Proceedings of the 33rd Annual General Meeting of the British Institute of Non-Destructive Testing, 2008
I. Williams, D. Svoboda, N. Bowring and E. Guest, “Statistical Edge Detection of Concealed Weapons Using Artificial Neural Networks”. In Proceedings of SPIE-IS&T Electronic Imaging. Vol. 6812. Bellingham, Washington: SPIE, 2008; p68121J-1-12, 12 pp. ISSN 0277-786X
I. Williams, D. Svoboda, N. Bowring and E. Guest, “Improved Statistical Edge Detection Through Neural Networks”. In 10th Conference on Medical Image Understanding and Analysis 2006. ISBN: 1-901727-31-9; p56-60
D. Svoboda, I. Williams, N. Bowring and E. Guest, “Statistical Techniques for Edge Detection in Histological Images”. In 1st Int. Conf. on VISAPP – International Conference on Computer Vision Theory and Applications 2006. ISBN: 972-8865-40-6; p457 462
I. Williams, N. J. Bowring, E. Guest, P. Twigg, Y. Fan and D. Gadsby, “A Combined Statistical/Neural Network Multi-Scale Edge Detector”. In 5th IASTED Visualization Imaging and Image Processing Conf. 2005. ISBN: 0-88986-528-0; p480-266
D. Gadsby, P. Twigg, N. Bowring and I. Williams, “Ultra Wideband Positioning for Intelligent Security Systems”. The Journal for the Institute of Measurement and Control. Volume 38, p140-146. 2005.
Robinson J.E., Athwal C.S. and van Reeven V., “Analysing Engine Behavior Through High Speed Video”, Engine Expo, Stuttgart, 2005
J. D. Foss, “Dynamic Intelligent Intermediation”; invited presentation to BBC Technology Forum, December 2005
J. D. Foss, “Beyond MultiPlay”; invited presentation to BBC Technology Forum, February 2005
J. D. Foss, “From Triple Play to the Global Jukebox”; invited presentation to BBC Technology Forum, July 2004
Robinson J.E. and Athwal C.S., “Measurement of Accessory Drivebelt Oscillations via High Speed Imaging”, Advanced Powertrain Control Symposium, Birmingham, 2004
Athwal C.S. and Robinson J., “Synchronised Multimedia for Engineering and Scientific Analysis”, Multimedia Systems Journal, 9, 365-377
Hough, G., Athwal, C., Williams, I., 2015. Fidelity and Plausibility of bimanual Interaction in Mixed Reality, IEEE Transactions on Visualisation and Computer Graphics, 2015
Smith, Samuel; Williams, Ian. A Statistical Method for Surface Detection. In proceeding of Eurographics Workshop on Visual Computing for Biology and Medicine, 2015.
S. Smith and I. Williams, "A Statistical Method for Improved 3D Surface Detection," in IEEE Signal Processing Letters, vol. 22, no. 8, pp. 1045-1049, Aug. 2015.