Page 14 - Classification Parameter Estimation & State Estimation An Engg Approach Using MATLAB

THE SCOPE OF THE BOOK 3

1.1.1 Classification

The title of the book already indicates the three main subtopics it will cover:
classification, parameter estimation and state estimation. In classification,
one tries to assign a class label to an object, a physical process, or an event.
Figure 1.1 illustrates the concept. In a speeding detector, the sensors are
a radar speed detector and a high-resolution camera, placed in a box beside
a road. When the radar detects a car approaching at too high a velocity
(a parameter estimation problem), the camera is signalled to acquire an
image of the car. The system should then recognize the license plate, so that
the driver of the car can be fined for the speeding violation. The system
should be robust to differences in car model, illumination, weather circum-
stances etc., so some pre-processing is necessary: locating the license plate in
the image, segmenting the individual characters and converting it into a
binary image. The problem then breaks down to a number of individual
classification problems. For each of the locations on the license plate, the
input consists of a binary image of a character, normalized for size, skew/
rotation and intensity. The desired output is the label of the true character,
i.e. one of ‘A’, ‘B’,.. ., ‘Z’, ‘0’,.. ., ‘9’.
Detection is a special case of classification. Here, only two class labels
are available, e.g. ‘yes’ and ‘no’. An example is a quality control system
that approves the products of a manufacturer, or refuses them. A second
problem closely related to classification is identification: the act of
proving that an object-under-test and a second object that is previously
seen, are the same. Usually, there is a large database of previously seen
objects to choose from. An example is biometric identification, e.g.

Figure 1.1 License plate recognition: a classification problem with noisy measurements