Skip to main content

Sallama Athab - Parallel Priority Region Approach to Detect Background

Sallama Athab joined the School of Science and Technology University of Northampton as a PhD research visitor from University of Babylon on a six-moth visit. The purpose of her visit is to develop her PhD research further whilst at Northampton. 

Up-coming paper:
 Sallama Athab ,Hala Bahja, Yinghui Zhang (2013) 
"Parallel Priority Region Approach to Detect Background" 
Oral Presentation 
ICCCISE 2013: International Conference on Computer, Communication and Information Sciences and Engineering. 
Paris, France, 7-8 October 2013

Background detection is essential in video analyses; optimization is often needed to achieve the real time calculation. Information gathered by dual cameras placed in the front and rear part of Autonomous Vehicle (AV) are integrated for background detection. In this paper, real time calculation is achieved on the proposed technique by using Priority Regions (PR) and Parallel Processing together where each frame is divided into regions then each region process in parallel. PR division depends upon driver view limitation. Background detection system built on the Temporal Difference (TD) and Gaussian Filtering (GF). Temporal Difference and Gaussian Filtering with multi threshold and sigma(weight) value are be based on PR characterize. Experiment result is prepared on real scene. Comparison of the speed and accuracy with traditional background detection techniques, effectiveness of PR and parallel processing are discussed in this paper as well.

Sallama Athab - Filter to Detect Objects in Video from Moving Platform


Popular posts from this blog

Experiments in teaching Neural Networks

Excel Based

More details available at including links to the code.

All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon

Social Analysis of Publications

The Computing staff's network of co-authors, at the University of Northampton, based on the University's  research repository NECTAR - on 12th November 2016. The data goes back to 2010.

The data was analysed using the software VOSviewer - free software for visualising networks. Differences in colours represents, the clusters of publications with those authors picked out by the software. The relative size of the circles is the relative number of publications listed; so for the two biggest circles/hubs it relates to 55 and 34 publications in this time period. Some relatively new authors, to the University but not to research, explains some of the 'islands' and the number of publications within it - it only reflects publications whilst at the University of Northampton.

To dig a little deeper, going to  look at the two biggest 'hubs' through their NECTAR records, so potentially going …

Computer lecturer’s research helps improve the next generation of technology

Taken from: A computing lecturer at the University of Northampton, who is researching into how the efficiency of our everyday devices, such as mobile phones, can be improved, has been awarded the best paper at two recent conferences. Dr Michael Opoku Agyeman has written several journal papers focusing on how the next generation of technology can meet the ever increasing demands from consumers. He was invited to present his work at the 19th Euromicro Conference on Digital System Design in Cyprus and the Institute of Electrical and Electronics Engineers’ 14th International Conference in Paris. Part of his research concentrates on whether several processing elements can be incorporated on a single chip, known as System-On-Chip, to improve the efficiency and speed of the computing systems that we use every day, from mobile phones to video-game consoles and even medical equipment…