Document Type : Research Paper
Authors
1 General Company for Electronic Systems, Baghdad, Iraq
2 Electrical Engineering Department, University of Technology, Baghdad, Iraq
Abstract
Multi-Object Detection and Tracking (MODT) are essential in many
application fields. Still, many enhancements in the speed of detection and tracking were
required to overcome the challenges during implementation. This paper presents a new
algorithm system for (MODT) to improve the execution time to be robust in real-time
applications. A background subtraction detection algorithm with a Kalman filter was
used to track and predict the object position and speed parameters. To improve the
processing time, its needs to reduce some frames in a way that does not affect the
detection accuracy too much and instead use the prediction and the estimated value
obtained based on the Kalman filter for the tracked object. This work uses a single video
camera to show how effectively to compute and detect multiple objects concurrently; it is
applied for daytime preprocessing in an automated traffic surveillance system.
Preliminary testing findings show that the suggested algorithm for this vehicle monitoring
system is feasible and effective. It illustrates that using the suggested algorithm with a
single video camera can simultaneously watch, detect, and track several vehicles and
improve execution time. Simulation results on the built system demonstrate that the
proposed system reduced the execution time to approximately 41.5% compared to the
standard background subtraction algorithm. Results indicate the proposed algorithm has
an approximate error for the position and speed of detected and tracked objects compared
with the standard background subtraction algorithm.
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