Welcome to Biomedical Image Processing Lab (BIPL)!


Principal Investigator:

Dr. Huiyu (Joe) Zhou (Homepage)

Centre for Data Sciences and Scalable Computing

The Institute of Electronics, Communications and Information Technology (ECIT)

School of Electronics, Electrical Engineering and Computer Science

Queen's University of Belfast

Belfast, BT3 9DT

United Kingdom



  • Our team is part of the consortium that has been awarded a H2020 research grant to work on "Smart distribution grid: a market driven approach for the next generation of advanced operation models and services" (DOMINOES), 15 May 2017.
  • We are now recruiting two research fellows for cancer diagnosis, working with Phillips Ltd. Please click this Link for more details. Application deadline (closed): 05 June 2017.
  • Our lab is recruiting PhD students (open for 2017):
  • We are awarded a Pump-Prime Fund from the Alzheimer Research UK, working on mouse behaviour analysis, 6 May, 2017.
  • We are awarded a Service Development Grant from the Puffin Trust, working on foetus movement detection, 5 May, 2017.
  • Dr. H. Zhou serves as a Guest Editor of IEEE Communications Magazine on the topic "Advanced industrial wireless sensor networks and intelligent IOT", submission due on 1 July, 2017.
  • Dr. H. Zhou serves as a Guest Editor of Journal of Skin Cancer on the topic "Computational challenges in skin cancer: from acquisition to diagnosis", submission due on 8 September, 2017.
  • Prof. Xuelong Li and his team will closely work with us with the support of Royal Society-Newton Advanced Fellowship during 2017-2020 on "Video traffic analysis for abnormal event detection", March, 2017.
  • Our lab currently works with Dr. Paul Best from AHSS for a research project on online health service utilisation, supported by Faculty Research Initiatives Fund of QUB, February, 2017. 
  • Dr. Haiping Ma, sponsored by the CSC Scheme,works within our lab from November 2016 for one year. 
  • Previous updates.
Call for Papers

Introduction      Teaching      Research      Selected Publications      Team members      Presentation


Our biomedical image processing group mainly works on the development of novel algorithms and application tools for automated processing of medical and biological images. Research topics of interest include image segmentation, object detection and tracking, 3-D reconstruction and information retrieval. Our research contribution is made towards two complementary aspects:

  • Fundamental understanding and modelling of biomedical images;
  • Application-driven development in collaboration with professionals in medicine and biology.   
With digital biomedical signals/images increasingly being stored and shared in networks, our research group also looks to bolster the analysis of biomedical data and cyber-security of signal processing systems.

  • Web and Mobile App Development (CSC3054/7054). Spring, 2017.
  • Web and Mobile App Development (CSC3054/7054). Spring, 2016.
  • Web and Mobile App Development (CSC3054/7054). Spring, 2015. 
  • Web and Mobile App Development (CSC3054/7054). Spring, 2014. 
  • Web and Mobile App Development (CSC7054). Spring, 2013. 
  • Emerging Human Based Security: Biometrics (CSC7002). Spring, 2010. 


Current Funded Projects: 

  • Puffin Trust: Fetal movement analysis in ultrasonic videos, 2017-2018, Queen's University of Belfast, United Kingdom.
    • We aim to design an automated system to analyse the movement of a fetus so that any abnormal event can be handled as soon as possible.
  • Royal Society-Newton Advanced FellowshipVideo traffic analysis for abnormal event detection, 2017-2020, Queen's University of Belfast, United Kingdom.
    • This project aims to design a new automated system in order to correctly track multiple vehicles in a camera network, reliably cluster motion trajectories of the vehicles into different categories and robustly predict the events of the vehicles in crowd scenarios.   
  • Agri-Food Quest: Plasmofluidic analytical device: a rapid point-of-sampling diagnostic and management support platform for infectious and antimicrobial resistant pathogens, 2016-2018, Queen's University of Belfast, United Kingdom. 
    • This project aims to develop an innovative plasmofluidic paper-based analytical device prototype with the support of image analysis that can provide a specific, sensitive and multiplex detection of infectious pathogens (i.e. Escherichia coli, Campylobacter and Staphylococcus aureus species) and their antimicrobial resistance (AMR) profiles.
  • EPSRC QUBAN Programme: Mobile plasmofluidic paper-based analytical device: A rapid diagnostic and management support platform to combat multi-drug resistance for resource-poor settings, 2016, Queen's University of Belfast, United Kingdom. 
    • This project aims at the development and assessment of a plasmonic microfluidic paper-based analytical device compatible with mobile phone and image analysis technologies for label-free, ultra-sensitive and multiplexing detection of MDR Escherichia coli.
  • H2020-MSCA-ITN-2016: Smartphone analyzers for on-site testing of food quality and safety, 2017-2020, Queen's University of Belfast, United Kingdom. 
    • The objectives of this project is to develop smartphone and camera based bio-analytical sensing and diagnostics tools for simplified on-site rapid pre-screening of food quality and safety parameters and wireless data transfer to servers of relevant of stakeholders.
  • B-Secur: Feasibility study of biometrics identification algorithms, 2016, Queen's University of Belfast, United Kingdom. 
    • The objectives of this project is to evaluate recently developed algorithms for biometrics identification. 
    • Team member: Pushpinder Chouhan.
  • Invest NI/Philips: Pathological cancer image analysis, 2016-2019, Queen's University of Belfast, United Kingdom. 
    • The objectives of this project is to develop new feature representation and classification algorithms for identifying cancerous and non-cancerous areas in pathological images.
  • EPSRC/Innovate UK/Invest NI/Industry (EP/N508664/1): The Centre for Secure Information Technology (CSIT 2), 2015-2020, Queen's University of Belfast, United Kingdom. 
    • The main objective of this project is to establish a global innovation hub for cyber security in order to promote growth in this strategically important sector of the UK economy. In our group, we expect to develop novel machine learning techniques to achieve anomaly detection for smart city infrastructure. 
    • Team member: Sriram Varadarajan.
  • EPSRC (EP/N011074/1): Automated mouse behaviour recognition, 2015-present, Queen's University of Belfast, United Kingdom. 
    • The main objective of this project is to design an automated system for detecting and tracking multiple mice, followed by recognition of mouse behaviours including their communication.
    • Team members: Jack Ferguson, David Fullerton and Zheheng Jiang.
  • China Scholarship Council (CSC): Object detection and tracking, 2015-2016, Queen's University of Belfast, United Kingdom.  
    • The aims of this project include integration of multiple features for trajectory clustering using a Markov Chain approach, and multi-animal localisation in the scene.
    • Team member: Hailin Li
  • DEL studentship: Development of a portable platform for the detection of antibiotic-resistant bacteria in seafood, 2016-2019, Queen's University of Belfast, United Kingdom.  
    • The objectives are to develop an innovative sensing technology based on enzyme-amplified aggregation of plasmonic nanoparticle to produce a distinct colour signal that can be processed by a handheld image processing device. 
    • Team member: Natasha Logan.
  • China Scholarship Council (CSC): Identification of Non-Invasive Tumour In Human Tissue, 2014-2015, Queen's University of Belfast, United Kingdom. 
    • In this project, we are interested to identify tumour on Haematoxylin & Eosin stained sections, which grow beyond their source into the surrounding normal healthy tissue.
    • Team member: Kun Zhang.
Previous Projects: 

  • EPSRC: The Centre for Secure Information Technology (CSIT 1): Security Convergence For Transport Corridors, 2009-2015, Queen's University of Belfast, United Kingdom
    • In this Grand Challenge, we designed a novel event driven computing system that can detect and process events using a heterogeneous sensor network (e.g. CCTV hardware and other security devices). This system has been applied to two major application areas, i.e. a bus and an airport departure lounge.
    • I was leading WP7 on Event Search and Retrieval. Team members: Sriram Varadarajan, Jeong-Gyoo Kim, and Xin Hong
  • EPSRC: ISIS - An Integrated Sensor Information System for Crime Prevention, 2009-2010, Queen's University of Belfast, United Kingdom
    • The ISIS project targeted at detecting threats on public transport, informing key decision makers of the threats and managing its own networks. This project used video cameras, audio microphones and RF/microwave sensors to detect threats as they enter buses or trains. In cases where the passenger is unknown, the developed system also used advanced RF scanning techniques to check for external intrusion into the security zone. The novel contribution of this project consists of automatic human profiling and three dimensional object tracking.
  • EU FP6: RUSHES - Retrieval of Multimedia Semantic Units for Enhanced Reusability, 2007-2009, Brunel University, United Kingdom 
    • The aim of the RUSHES project was to design, implement and validate a system for indexing, accessing and delivering raw, unedited audio-visual footage known in the broadcasting industry as "rushes". This project was intended to promote the reuse of such material and especially its content in the production of new multimedia assets by offering semantic media search capabilities. The major contribution includes techniques for automatic content cataloguing and semantic based indexing, knowledge extraction for semantic inference, semantic based content annotation and interactive navigation.
    • Team members: Mohammad Rafiq Swash, Jawid Azizi, Umar A. Sadiq, and Richard M. Jiang 
  • EPSRC: MOTINAS - Multi-model Object Tracking in A Network of Audio-Visual Sensors, 2006-2007, Queen Mary College, University of London, United Kingdom
    • The aim of this project was to develop a novel scheme for multi-model and multi-sensor tracking. The multi-sensor network is composed of STAC sensors (stereo microphones coupled with rectilinear, omni-directional or pan-tilt-zoom cameras). Sound information is used to discriminate ambiguous visual observation as well as to extend the coverage area of the sensors beyond the field of view of the cameras. The major contribution is a robust and adaptive representation of objects based on their acoustical and visual attributes, while the objects are moving across the network of heterogeneous sensors.   
  • EPSRC: SMART Rehabilitation - Technological Applications for Home Based Stroke Patients, 2004-2006, University of Essex, United Kingdom
    • The aim of this project was to explore how technology could be used to facilitate active in-home rehabilitation for people following stroke. We used orientation sensors that were attached to the wrist and upper limb through clothing. The major contribution of the project is a sensor fusion strategy accompanied by a decision support interface (TV or computer screen) for stroke rehabilitation.
    • Team member: Yaqin Tao          
  • Efficient Ego-Motion Tracking And Obstacle Detection Using Gait Analysis, 2000-2004, Supported by A Multi-Disciplinary Studentship of Heriot-Watt University, United Kingdom
    • The purpose of this study was to design systems that could be used to aid elderly or visually impaired people when they have difficulty in detecting potential tripping hazards. A human gait-based methodology was developed to represent camera motion as a truncated Fourier series. To parameterise this unknown non-linear motion model, we first establish the history of the camera (or human) motion using a classical frame-by-frame analysis, and then apply the iteratively-reweighted least-squares technique for recovery of the motion model. Using the retrieved gait, we undertake an extended "predict-correct" framework (the maximum a posteriori strategy) in order to obtain robust motion estimates. Assuming that the camera position in space has been properly established, we then use this knowledge in combination with the camera motion to construct a safe path ahead of the pedestrian by considering a simple projective invariant analysis.
  • Fast Three-Dimensional Imaging Techniques in Echocardiography, 2004-2007, Co-Investigator, Supported by The Guangxi Natural Science Foundation of China
    • The aim of this project was to propose a novel approach for reconstructing the three dimensional structure of a human heart from two dimensional images. Tracking the variations of the structure is used to analyse the dynamics of the heart. Our contribution consists of new techniques for image denoising, structure from motion, image segmentation and object tracking.   
  • Fuzzy C-Means Algorithms For Image Segmentation And Quantisation, 2008-2011, Queen's University of Belfast, United Kingdom
    • This project was in an attempt to seek optimal solutions towards the challenging over- or under-segmentation (or quantisation) problem. We proposed several new schemes for achieving better performance than the other state of the art strategies. The proposed approaches have been evaluated using publicly accessible databases.

Selected Publications 

(Complete list of the publications can be found on: University Website and Google Scholar) 

Team members 

 Current members:

  • Dr. Xun Chen, academic visitor. Project: Underwater object visual detection and recognition, 2017-2018. 
  • Dr. Emre Dandil, academic visitor. Project: Fetal movement analysis, 2016-2017.
  • Zeynep Kurugollu, MSc student. Project: A colorimeter application for food toxin detection, 2016-2017.
  • Bingchi Luo, academic visitor. Project: Enhancing the privacy of video surveillance, 2016-2017.
  • John Giron, Joshua Green, David Mason and Lei Tong, final year students. Project: Gait-based gender recognition, 2016-2017.
  • Mr. Andrew Moyes, PhD student. Project: Medical Image Analysis, 2016-2019.
  • Ms. Hui Zhu, academic visitor. Project: Audiovisual signal processing, 2016-2017.
  • Mr. Li Liu, academic visitor. Project: Audiovisual signal processing, 2016-2017.
  • Dr. Hailin Li, academic visitor. Project: Motion trajectory clustering, 2015-2016.
  • Dr. Rong Dong, academic visitor. Project: Rainfall measurement, 2016.
  • Natasha Logan, PhD student. Project: Development of a portable platform for the detection of antibiotic-resistant bacteria in seafood, 2016-2019.
  • Zheheng Jiang, PhD student/research assistant. Project: Animal behaviour analysis, 2015-present.
  • Andy Park, Part-time PhD student. Project: Human detection from images, 2013-present.
  • Dr. Xin Hong, Research Fellow. Project: Event search and retrieval, 2012-present.
 Former members:
    • Dr. Sriram Varadarajan, Research Fellow. Project: Anomaly detection through graph matching, 2015-2016. 
    • Hugh Girvan and Ashley Simpson, MSc students. Project: Animal detection and recognition, 2016.
    • Cristina Surlea, Part-time PhD student. Project: Medical image segmentation, 2013-2015.
    • Chris McClune, MSc student. Project: MyPTApp, 2015.
    • David Fullerton and Zheheng Jiang, MSc students. Project: Animal behaviour analysis, 2015.
    • Jack Ferguson, MSc student. Project: Animal detection and tracking, 2015.
    • Kun Zhang, Visiting researcher. Project: Identification of non-invasive tumour in human tissue, 2014-2015.
    • Dr. Sriram Varadarajan, PhD project: Dynamic background modelling for foreground detection in surveillance video, 2010-2015.
    • Dr. Wenju Zhou, PhD project: Investigation and application of online high-speed visual inspection and precise control, 2010-2014, and now works at Ludong University, China.
    • Philip McShane, postgraduate student. Project: MYEA: Maximise your experience application, 2014, and now a PhD student in the School.
    • James Walmsley, postgraduate student. Project: MYEA: Maximise your experience application, 2014. 
    • Sean Egan, postgraduate student. Project: MMSEA: Make my shopping easier application, 2014, and now works at Allstate, Belfast. 
    • Jacek Studzinski, postgraduate student. Project: MMSEA: Make my shopping easier application, 2014, and now works at SR Labs, Belfast.
    • Alex Turnbull, undergraduate student. Project: Find your phone, 2013-2014, and now works at Kainos, Belfast. 
    • Sarah Dynan, undergraduate student. Project: Tour and object recognition application, 2013-2014, and now works at TotalMobile, Belfast.
    • Chris Walsh, undergraduate student. Project: Game engine component - AI path-finding library, 2012-2013.
    • James Blair, undergraduate student. Project: Procedural dungeon generator created in C# and Unity, 2012-2013.
    • Dr. Jeong-Gyoo Kim, Research Fellow. Project: Shape modelling and human detection, 2011-2013.
    • Dr. Jiali Shen, Engineer. Project: Multi-camera object tracking, 2010-2012, and now works at Fidessa, Belfast.
    • Carol Campbell, PhD student. Project: Video event recognition using temporal dynamics, 2009-2011, and now works at NYSE, Belfast.
     For education purposes:  

    • IEEE International Conference on Intelligent Systems (IEEE-IS), Sofia, Bulgaria, September, 2016. Tutorial.
    • International Conference on Advanced Electronic Science and Technology (AEST), Shenzhen, China, August, 2016. Keynote speech
    • The 8th International Conference on Computational Intelligence and Software Engineering (CiSE), Nanjing, China, May, 2016. Plenary speech
    • "Secure our society - Computer vision techniques for video surveillance", International Conference on Pattern Recognition Applications and Methods (ICPRAM), Rome, Italy, Feb. 2016. Tutorial.
    • "Computer vision techniques for video surveillance", VALSE Webinar, UK, 6 January, 2016. Invited talk.
    • "'Who are you?': human profiling and behaviour analysis", International Conference on Material Engineering and Mechanical Engineering, Hangzhou, China, October, 2015. Keynote speech.
    • "Evidence reasoning for event inference in smart transport video surveillance", Workshop on Video Soft Service, UCAMI/IWAAL, Belfast, United Kingdom, December, 2014. Invited talk.
    • "Evidence reasoning for event inference in smart transport video surveillance", Special session "Smart cameras for smart environments", Int'l Conf. on Distributed Smart Cameras, Venice, Italy, November, 2014.
    • "'Who are you?': human profiling and behaviour analysis", Ocean University of China, China University of Petroleum (Huadong) and Nanjing University of Aeronautics and Astronautics, China, September, 2014. Invited talk.
    • "Markov Chain Monte Carlo approaches in computer vision", Shanghai University, China, December, 2013. Invited talk.
    • "'Who are you?': human profiling and behaviour analysis", China-UK Symposium on Life System Modeling & Simulation, Colchester, United Kingdom, August, 2013. Keynote speech. 
    • "Computer vision techniques for video surveillance", IASTED International Conference on Computer Graphics and Imaging, Innsbruck, Austria, February, 2013. Tutorial.
    • "Human profiling and event recognition in video surveillance", University of Ulster, United Kingdom, February, 2012. Invited talk.
    • "Multimedia analysis and reuse of raw unedited audiovisual contents", Aston University, United Kingdom, January, 2009. Invited talk.
    • "Human motion tracking and rehabilitation", The Technology Partnership, Melbourn, United Kingdom, February, 2008. Invited talk.
    • "Audiovisual tracking using STAC sensors", University of Portsmouth, United Kingdom, December, 2007. Invited talk.
    • "Smart sensor for human movement tracking", The IEE Seminar on Sensor System for Intelligent Buildings, Birmingham, United Kingdom, November, 2004. Invited talk.
    • "Efficient motion tracking using gait analysis", McGill University, Montreal, Canada, May, 2004. Invited talk.

    Last modified by Huiyu Zhou: 12th June, 2017, United Kingdom.

    Huiyu Zhou,
    21 Sep 2012, 05:27
    Huiyu Zhou,
    1 Apr 2017, 09:51
    defect detection of bottle caps.avi.rar
    Huiyu Zhou,
    20 Mar 2014, 07:33