Image Processing Reference
In-Depth Information
7
Object description
7.1
Overview
Objects are represented as a collection of pixels in an image. Thus, for purposes of recognition
we need to describe the properties of groups of pixels. The description is often just a set of
numbers - the object's
descriptors
. From these, we can compare and recognise objects by
simply matching the descriptors of objects in an image against the descriptors of known
objects. However, in order to be useful for recognition, descriptors should have four important
properties. First, they should define a
complete set
. That is, two objects must have the same
descriptors if and only if they have the same shape. Secondly, they should be
congruent.
As
such, we should be able to recognise
similar
objects when they have
similar
descriptors.
Thirdly, it is convenient that they have
invariant
properties. For example,
rotation
invariant
descriptors will be useful for recognising objects whatever their
orientation
. Other important
invariance properties naturally include scale and position and also invariance to affine and
perspective changes. These last two properties are very important when recognising objects
observed from different viewpoints. In addition to these three properties, the descriptors
should be a
compact
set. Namely, a descriptor should represent the essence of an object in
an efficient way. That is, it should only contain information about what makes an object
unique, or different from the other objects. The quantity of information used to describe
this characterisation should be less than the information necessary to have a complete
description of the object itself. Unfortunately, there is no set of complete and compact
descriptors to characterise general objects. Thus, the best recognition performance is obtained
by carefully selected properties. As such, the process of recognition is strongly related to
each particular application with a particular type of object.
In this chapter, we present the characterisation of objects by two forms of descriptors.
These descriptors are summarised in Table
7.1
.
Region
and
shape
descriptors characterise
Table 7.1
Overview of Chapter 7
Chain codes
Shape boundary
Cumulative angular function
Fourier descriptors
Elliptic descriptors
Object description
Area
Perimeter
Basic
Compactness
Region
Dispersion
First order
Moments
Centralised
Zernike