Technology Background

Computer vision is the science and technology of machines that see (i.e. a machine is able to extract information from an image that is necessary to solve some task).

After a 5 years in industry (Industrial and Scientific Imaging (ISI) Ltd., Limerick, Video Tek, New Jersey (USA),Westinghouse Electric Systems & Logistics (WESL) Ltd., Shannon) I formed the Vision Systems Group (VSG) (1990), as a forum to co-ordinate and support the promotion of computer and machine vision research in Dublin City University (DCU). In 1999 I expanded our industrial work and developed the  Medical Imaging and Visualization Laboratory as a focus for medical imaging research within DCU. The Vision Systems Group currently consists of a core team working on computer vision (specifically image segmentation), medical imaging (specifically computer aided detection / diagnosis) and their associated visualization projects. The VSG was a founding member of Irish Pattern Recognition and Classification Society (IPRCS).

VSG was a founding member RINCE - an Irish national research institute focussed on innovation in engineering(a €10.4 million HEA-PRTLI I initiative). It was also founding member of the NBIP - National Biophotonics & Imaging Platform (a €30 million HEA-PRTLI IV initiative). It is a member of the DOCTRID (Daughters of Charity – Technology, Research into Disability) Research Institute (RI) and a host institution for the Marie Curie ASSISTID EU COFUND focusing on research is into Assistive Technologies for people with Autism and Intellectual Disabilities.

My digital and non-digital computer vision research programmes relate to issues involved in the acquisition (custom sensor design), processing, quantitative analysis, classification (machine and deep learning), visualization and systems engineering (integration) for a wide range of computer vision applications. Specifically his research focuses on the issues involved in the automation or semi automation of image feature segmentation, machine learning and its associated quantitative analysis and classification, at both a micro and macro level. This work is grounded in the need to develop reliable and robust working solutions to real problems.


I focus on advanced needs driven image segmentation, and associated quantitative analysis (specifically mathematical morphology, colour-texture analysis) research with applications in computer/machine vision and medical imaging (specifically computer aided detection and diagnosis focusing on translational research). This is done within an engineering framework focusing on the automatic extraction of key image features with a view to quantitative analysis, classification/learning and/or tracking of key information within an image or sequence of images.

Theoretical Focus: Image segmentation, and its associated quantitative analysis (specifically mathematical morphology and colour-texture analysis) and classification.

Application Focus: Computer Vision projects (including industrial vision, hyperspectral image analysis, deep learning based computer vision,modelling and removal of distortions in images, computer aided detection of reproductive cycle and pregnancy of bovines, and the calibration of non-conventional camera configurations); Biomedical Image Analysis Projects (specificallydeveloping diagnostic computer vision tools for translational research focusing on ever earlier stages of the disease manifestation i.e. from surface to organ to cell and sub cell imaging).

  • Surface: The analysis of three-dimensional facial dysmorphology
  • Organ: White Matter Volume assessment in premature infants on MRI at term and 2 years age – Computer Aided Volume Analysis
  • Organ: CAD (Computer Aided Diagnosis) for ultrasound analysis of the carotid artery
  • Cell: Automatic tracking of cell migrationfor molecular biology applications using time-lapse images - in vivo, in vitro and ex vivo
  • Sub-cell: Automated segmentation/classification of mitochondria from TEM (Electron Microscopy) images

Funding Support from: EU Fifth Framework Programme IST: Accompanying Measures; Motorola; Hewlett-Packard; Amdahl; Agilent-Ireland; Technology Systems International Ltd.; Tegral; Forbairt; European Commission: Framework IV; EOLAS/British Council; DCU Research Committee; DCU Educational Trust; RINCE; Irish Cancer Society; Mater Hospital; National Rehabilitation Board; Private Donors; Albert College Junior and Senior Fellowships; Health Research Board; Irish Research Council for Science; Engineering and Technology (IRCSET); NBIP; Enterprise Ireland (C+, Tech Dev, POC, ARGS); Irish Higher Education Authority (PRTLI I, IV, V); Wellcome Trust; Temple Street Children's Hospital; Industrial partners, Science Foundation Ireland (PI & RFP), and Marie-Curie FP7.

I have hosted visiting international researchers from: NIT Karnataka (India); Universidad de Deusto (Spain); ENSEEIHT (France); Robotiker (Spain); University of Vigo (Spain); University of Western Ontario (Canada); Transilvania University (Romania); University of Tuzla (Bosnia and Herzegovina); Fachhochschule (FH) Mannheim (Mannheim University Of Applied Sciences, Germany); Ecole Nationale Superieure des Techniques Industrielles et des Mines d'ALES (France); Cardiff University (Wales).

 Selected Project Profiles

 Computer Vision

  • Deep learning for texture and dynamic texture analysis
  • Roadis: Removal of Optical Aberrations in Digital Imaging Systems.
  • Correction of Lateral Chromatic Aberration through Calibrated Demosaicing of Digital Images
  • CTEX: Adaptive colour-texture discriminators for robust image segmentation
  • Development of a computational model for the description of the shape, texture and dynamics of facial expression.
  • Multi-Resolution Invariant Analysis for Robust Texture Classification
  • Calibration of Non-conventional Imaging Systems
  • Content Based Image Pose Manipulation
  • Unsupervised Segmentation of Natural Images Based on the Adaptive Integration of Colour-Texture Descriptors
  • The application of manifold based visual speech units for visual speech recognition
  • Accelerated Volumetric Reconstruction From Uncalibrated Camera View
  • Modelling and Removal of Distortions in Images
  • A Generic Framework for Colour Texture Segmentation
  • NeatVision: Rapid Prototyping for Image Processing & Analysis
  • VSG Image Processing & Analysis Toolbox (VSG IPA TOOLBOX) for MATLAB

Biomedical Computer Vision (Computer Aided Detection and Diagnosis focusing on Translational research)

  • CAD (Computer Aided Diagnosis) for Ultrasound Analysis of the Carotid Artery
  • Pumping Lymphatic / Vessel Motion Tracking
  • Full Body Imaging (MRI)
  • Quantitative / Motion Analysis of Cells from Time Lapse Image Sequences
  • Automated Deformation Modelling for Cellular Structures
  • Automated Segmentation and Classification of Mitochondria from TEM Images
  • Cardiac Functionality Imaging (MRI) (3D/4D)
  • Computer Aided Diagnosis: Lung/Nodule Detection
  • The analysis of three-dimensional facial dysmorphology.
  • White Matter Volume assessment in premature infants on MRI at term and 2 years age – Computer Aided Volume Analysis
  • Enhanced Computer Assisted Detection of Polyps in CT Colonography
  • Automated Flat Polyps Detection
  • Electronic Cleansing for CAD-CTC
  • Analysis of Cardiac Magnetic Resonance Images
  • Computer Aided Diagnosis for CT Colonography CAD-CTC
  • Automatic polyp detection using curvature analysis for standard and low-dose CT (Computed Tomography) data
  • Efficient Pre- segmentation Filtering In MRCP
  • Brain Region Segmentation (MRI)
  • OSMIA - Open Source Medical Image Analysis
  • 3D modelling for functional analysis of cardiac images (FACI)

Industrial / Machine Vision

  • Automatic computer aided detection of reproductive cycle and pregnancy of Bovines from ultrasound images.
  • Granite Texture Classification
  • Classification of materials through the integration of spectral and spatial features from hyperspectral data
  • Inspection Solutions for Grading Painted Slates
  • Watermark (Paper) Localisation
  • A Real-time Low-cost Vision Sensor for Robotic Bin Picking
  • Automated packing of arbitrary shapes
  • AOIS- Automated Optical Inspection Systems
  • Visually Guided Robotic Mobile Platforms
  • 3D Imaging

Innovation And Enterprise

As an engineer I am keen to get ideas from the Lab into the marketplace. some of our recent successes are listed below.

  • Winner 2014 Award for engagement with industry/business for the licensing of its computer aided ultrasound detection technology to a new start-up ReproInfo Ltd.
  • Winner of DCU INVENT Commercialization Award 2010 for Jaliko Ltd. (a CIPA spin-out company)
  • Winner of the DCU INVENT (ICT/Engineering Section) Invention Disclosure Award 2007 & 2008.
  • 7 Invention Disclosures, 7 Patents filed.
  • 2 spin-out companies from the group
  • 4 technology licenses, 2 of which are royalty bearing.

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