Image Processing Reference
In-Depth Information
Fig. 8.6 Image differencing.
The effect of changing the
reference image
It should also be noticed that when the object is overlapping in the reference and
current image, then we only detect a part of the object, as seen in Fig. 8.6 .Ifwe
know the size and speed of the object we can calculate how long time there should
be between the reference image and the current image to avoid overlap. Or in other
words, the reference image need not be the previous image T
=−
1, it can also be
for example T
=−
5, see Fig. 8.6 .
8.5
Further Information
Video compression has for a long time been a cornerstone in video acquisition and
allowed for transmission and storage of video data. Video compression is a research
field in its own right and contains many more aspects than those basics presented
in this chapter. The interested reader is referred to a textbook dedicated to exactly
this field, see for example [17]. As the hardware and software has matured it has
become possible to capture, transmit and store larger and larger amounts of video
data. But even with today's fast computers, clever transmission systems, and huge
storage facilities, the handling of video data can still be too difficult and a reduced
framerate/resolution/quality is necessary. To appreciate this fact just imagine the
amount of video data captured, transmitted and stored in a surveillance setup with
for example 100 cameras.
Background subtraction can be a powerful allied when it comes to segmenting
objects in a scene. The method, however, has some build-in limitations that are
exposed especially when processing video of outdoor scenes. First of all, the method
requires the background to be empty when learning the background model for each
pixel. This can be a challenge in a natural scene where moving objects may always
be present. One solution is to median filter all training samples for each pixel. This
will eliminated pixels where an object is moving through the scene and the resulting
model of the pixel will be a true background pixel. An extension is to first order all
training pixels (as done in the median filter) and then calculate the average of the
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