  Image processing and recognition are an important part of the modern society,
with applications in fields such as advanced artificial intelligence, smart
assistants, and security surveillance. The essential first step involved in
almost all the visual tasks is background subtraction with a static camera.
Ensuring that this critical step is performed in the most efficient manner
would therefore improve all aspects related to objects recognition and
tracking, behavior comprehension, etc.. Although background subtraction method
has been applied for many years, its application suffers from real-time
requirement. In this letter, we present a novel approach in implementing the
background subtraction. The proposed method uses compressed, low-resolution
grayscale image for the background subtraction. These low-resolution grayscale
images were found to preserve the salient information very well. To verify the
feasibility of our methodology, two prevalent methods, ViBe and GMM, are used
in the experiment. The results of the proposed methodology confirm the
effectiveness of our approach.
