Image segmentation using adaptive video analytics, Image processingUS 9047677 B2

Patent


Sedky, Mohamed Hamed Ismail, Chibelushi, Claude Chilufya and Moniri, M. 2015. Image segmentation using adaptive video analytics, Image processingUS 9047677 B2. US 13/140,378
AuthorsSedky, Mohamed Hamed Ismail, Chibelushi, Claude Chilufya and Moniri, M.
Patent IDUS 13/140,378
Abstract

An image segmentation method has a training phase and a segmentation phase. In the training phase, a frame of pixellated data from a camera is processed using information on camera characteristics to render it camera independent. The camera independent data are processed using a chosen value of illuminant spectral characteristics to derive reflectivity data of the items in the image. Pixels of high reflectivity are established. Then, using data from the high reflectivity pixels, the actual illuminant spectral characteristics are established. The illuminant data are then processed to determine information on the illumination of the scene represented by the frame of pixellated data to derive reflectivity data of the scene. The segmentation phase comprises operating on a subsequent frame of pixellated data to render it camera independent and using the determined illumination information to process the camera independent data to determine reflectivity data of the scene to derive a foreground mask.

Year2015
Publication dates
Print02 Jun 2015
Publication process dates
Deposited23 Aug 2017
Permalink -

https://repository.uel.ac.uk/item/855x3

  • 99
    total views
  • 0
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

Convolutional Recurrent Smart Speech Enhancement Architecture for Hearing Aids
Abdallah Abdelhafiz Nossier, S., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2022. Convolutional Recurrent Smart Speech Enhancement Architecture for Hearing Aids. INTERSPEECH 2022. Incheon, Korea 18 - 22 Sep 2022
Two-Stage Deep Learning Approach for Speech Enhancement and Reconstruction in The Frequency and Time Domains
Nossier, S. A., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2022. Two-Stage Deep Learning Approach for Speech Enhancement and Reconstruction in The Frequency and Time Domains. WCCI 2022: IEEE World Congress on Computational Intelligence. Padua, Italy 23 May - 18 Jul 2022 IEEE. https://doi.org/10.1109/IJCNN55064.2022.9892355
A Mixed Reality Approach for dealing with the Video Fatigue of Online Meetings
Wall, J., Poobalasingam, V., Sharif, S., Moniri, M., Glackin, C. and Cannings, N. 2022. A Mixed Reality Approach for dealing with the Video Fatigue of Online Meetings. 7th International XR Conference. Lisbon, Portugal 27 - 29 Apr 2022
Resolving Ambiguity in Hedge Detection by Automatic Generation of Linguistic Rules
Goodluck Constance, T., Bajaj, N., Rajwadi, M., Maltby, H., Wall, J., Moniri, M., Woodruff, C., Laird, T., Laird, J., Glackin, C. and Cannings, N. 2021. Resolving Ambiguity in Hedge Detection by Automatic Generation of Linguistic Rules. 30th International Conference on Artificial Neural Networks (ICANN). Online 14 - 17 Sep 2021 Springer. https://doi.org/10.1007/978-3-030-86383-8_30
An Experimental Analysis of Deep Learning Architectures for Supervised Speech Enhancement
Nossier, S. A., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2020. An Experimental Analysis of Deep Learning Architectures for Supervised Speech Enhancement. Electronics. 10 (Art. 17). https://doi.org/10.3390/electronics10010017
Mapping and Masking Targets Comparison using Different Deep Learning based Speech Enhancement Architectures
Abdallah Abdelhafiz Nossier, S., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2020. Mapping and Masking Targets Comparison using Different Deep Learning based Speech Enhancement Architectures. 2020 International Joint Conference on Neural Networks (IJCNN). Glasgow, UK 19 - 24 Jul 2020 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206623
A Comparative Study of Time and Frequency Domain Approaches to Deep Learning based Speech Enhancement
Abdallah Abdelhafiz Nossier, S., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2020. A Comparative Study of Time and Frequency Domain Approaches to Deep Learning based Speech Enhancement. 2020 International Joint Conference on Neural Networks (IJCNN). Glasgow, UK 19 - 24 Jul 2020 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206928
Fraud detection in telephone conversations for financial services using linguistic features
Bajaj, N., Goodluck Constance, T., Rajwadi, M., Wall, J., Moniri, M., Glackin, C., Cannings, N., Woodruff, C. and Laird, J. 2019. Fraud detection in telephone conversations for financial services using linguistic features. Neural Information Processing Systems - NeurIPS 2019. Vancouver, Canada 08 - 14 Dec 2019 AI for Social Good Workshop NeurIPS.
A Framework for Augmented Reality Based Shared Experiences
Ali, A., Glackin, C., Cannings, N., Wall, J., Sharif, S. and Moniri, M. 2019. A Framework for Augmented Reality Based Shared Experiences. Immersive Learning Research Network - iLRN. London, UK 23 - 27 Jun 2019 Technischen Universit├Ąt Graz. https://doi.org/10.3217/978-3-85125-657-4-24
Comparative Analysis on the Competitiveness of Conventional and Compressive Sensing-based Query Processing
Fayed, Salema, Youssef, Sherin, El-Helw, Amr, Akbari, Akbar Sheikh, Patwary, Mohammad and Moniri, M. 2014. Comparative Analysis on the Competitiveness of Conventional and Compressive Sensing-based Query Processing. in: Advances in Information Science and Applications, Volume 1: Proceedings of the 18th International Conference on Computers (part of CSCC '14) Institute for Natural Sciences and Engineering (INASE).
Evaluation of Performance Enhancement for Crash Constellation Prediction via Car-to-Car Communication
Kuehbeck, Thomas, Hakobyan, Gor, Sikora, Axel, Chibelushi, Claude C. and Moniri, M. 2014. Evaluation of Performance Enhancement for Crash Constellation Prediction via Car-to-Car Communication. in: Communication Technologies for Vehicles Springer.
Compressive Sensing-based Target Tracking for Wireless Visual Sensor Networks
Fayed, Salema, Youssef, Sherin, El-Helw, Amr, Patwary, Mohammad and Moniri, M. 2014. Compressive Sensing-based Target Tracking for Wireless Visual Sensor Networks. in: Advances in Information Science and Applications, Volume I: Proceedings of the 18th International Conference on Computers (part of CSCC '14) Institute for Natural Sciences and Engineering (INASE).
Prediction architecture based on block matching statistics for mixed spatial-resolution multi-view video coding
Said, Hany, Moniri, M. and Chibelushi, Claude C. 2017. Prediction architecture based on block matching statistics for mixed spatial-resolution multi-view video coding. EURASIP Journal on Image and Video Processing. 2017 (1). https://doi.org/10.1186/s13640-017-0164-7
Analytical framework for Adaptive Compressive Sensing for Target Detection within Wireless Visual Sensor Networks
Fayed, Salema, Youssef, Sherin, El-Helw, Amr, Patwary, Mohammad and Moniri, M. 2017. Analytical framework for Adaptive Compressive Sensing for Target Detection within Wireless Visual Sensor Networks. Multimedia Tools and Applications. 77 (13), pp. 16533-16559. https://doi.org/10.1007/s11042-017-5227-3
A Hybrid Adaptive Compressive Sensing Model for Visual Tracking in Wireless Visual Sensor Networks
Fayed, Salema, Youssef, Sherin, El-Helw, Amr, Patwary, Mohammad and Moniri, M. 2015. A Hybrid Adaptive Compressive Sensing Model for Visual Tracking in Wireless Visual Sensor Networks. International Journal of Circuits, Systems, and Signal Processing. 9, pp. 134-144.
Adaptive compressive sensing for target tracking within wireless visual sensor networks-based surveillance applications
Fayed, Salema, M.Youssef, Sherin, El-Helw, Amr, Patwary, Mohammad and Moniri, M. 2015. Adaptive compressive sensing for target tracking within wireless visual sensor networks-based surveillance applications. Multimedia Tools and Applications. 75 (11), pp. 6347-6371. https://doi.org/10.1007/s11042-015-2575-8
Towards a fully automated monitoring system for Manhole Cover: Smart cities and IOT applications
Aly, Hesham H., Soliman, Abdel Hamid and Moniri, M. 2015. Towards a fully automated monitoring system for Manhole Cover: Smart cities and IOT applications. in: 2015 IEEE First International Smart Cities Conference (ISC2) IEEE. pp. 24-30
Spectral-360: A Physics-Based Technique for Change Detection
Sedky, Mohamed, Moniri, M. and Chibelushi, Claude C. 2014. Spectral-360: A Physics-Based Technique for Change Detection. 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2014). Columbus, OH, USA 23 - 28 Jun 2014 IEEE. pp. 405-408 https://doi.org/10.1109/CVPRW.2014.65