Maryam A. Yasir received her bachelor's degree in computer science from the University of Baghdad (UOB) -Iraq 2004. Since 2008, she is working as a lecturer at the computer science department, college of science, University of Baghdad up till now. In 2011 she received a certificate for a seven months course in IT Administration from the Technische Universität Berlin (TU)Berlin-Germany. In 2014 she received her master's degree in computer science from University Putra Malaysia (UPM)-Malaysia.She received her PhD in computer science from the University of Technology (UOT) -Iraq. Maryam has participated in many scholar courses and activities, local and abroad including Fulbright visiting scholar at the University of Central Oklahoma (UCO)-US 2015.
Computer science, Networks, Ad-hoc networks,Computer Vision, Object Detection
Multimedia
The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art
... Show More
(3)
(2)
Background subtraction is the dominant approach in the domain of moving object detection. Lots of research has been done to design or improve background subtraction models. However, there are a few well-known and state-of-the-art models that can be applied as a benchmark. Generally, these models are applied to different dataset benchmarks. Most of the time, choosing an appropriate dataset is challenging due to the lack of dataset availability and the tedious process of creating ground-truth frames for the sake of quantitative evaluation. Therefore, in this article, we collected local video scenes of a street and river taken by a stationary camera, focusing on dynamic background challenges. We presented a new technique for creati
... Show More
(1)