Human region segmentation and description methods for domiciliary healthcare monitoring using chromatic methodology

Ali A. Al-Temeemy

doi:10.1117/1.JEI.27.2.023005

6 March 2018 Human region segmentation and description methods for domiciliary healthcare monitoring using chromatic methodology

Ali A. Al-Temeemy

Author Affiliations +

Funded by: Al-Nahrain University, Liverpool University

Journal of Electronic Imaging, Vol. 27, Issue 2, 023005 (March 2018). https://doi.org/10.1117/1.JEI.27.2.023005

Abstract

A descriptor is proposed for use in domiciliary healthcare monitoring systems. The descriptor is produced from chromatic methodology to extract robust features from the monitoring system’s images. It has superior discrimination capabilities, is robust to events that normally disturb monitoring systems, and requires less computational time and storage space to achieve recognition. A method of human region segmentation is also used with this descriptor. The performance of the proposed descriptor was evaluated using experimental data sets, obtained through a series of experiments performed in the Centre for Intelligent Monitoring Systems, University of Liverpool. The evaluation results show high recognition performance for the proposed descriptor in comparison to traditional descriptors, such as moments invariant. The results also show the effectiveness of the proposed segmentation method regarding distortion effects associated with domiciliary healthcare systems.

Citation Download Citation

Ali A. Al-Temeemy "Human region segmentation and description methods for domiciliary healthcare monitoring using chromatic methodology," Journal of Electronic Imaging 27(2), 023005 (6 March 2018). https://doi.org/10.1117/1.JEI.27.2.023005

Received: 3 December 2017; Accepted: 14 February 2018; Published: 6 March 2018

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