-
英文资料翻译
Image
processing
is
not
a
one
step
process
．
We
are
able
to
distinguish
between several
steps which must be performed one after the other
until we can
extract the data of
interest from the observed
scene
．
In this way a
hierarchical
processing scheme is built
up as sketched in Fig
．
The figure gives an overview
of the different phases of image
processing.
Image processing begins
with the capture of an image with a
suitable
，
not
necessarily
optical
，
acquisition
system
．
In a technical or
scientific application
，
we
may choose to select an appropriate imaging system
．
Furthermore
，
we can set
up the illumination
system
，
choose the best
wavelength range
，
and select
other
options
to
capture
the
object
feature
of
interest
in
the
best
way
in
an
image
．
Once
the
image
is
sensed
，
it
must be
brought
into
a
form
that
can be
treated with digital process is called
digitization.
With
the
problems
of
traffic
are
more
and
more
serious.
Thus
Intelligent
Transport System (ITS) comes out. The
subject of the automatic recognition of
license plate is one of the most
significant subjects that are improved from the
connection
of
computer
vision
and
pattern
recognition.
The
image
imputed
to
the computer is disposed and analyzed
in order to localization the position and
recognition
the
characters
on
the
license
plate
express
these
characters
in
text
string
form
The
license
plate
recognition
system
(LPSR)
has
important
application in
ITS. In LPSR, the first step is for locating the
license plate in the
captured
image
which
is
very
important
for
character
recognition.
The
recognition
correction
rate
of
license
plate
is
governed
by
accurate
degree
of
license
plate location.
In
this
paper,
several
of
methods in image
manipulation
are compared
and analyzed, then come out the resolutions for
localization of the
car
plate.
The
experiences
show
that
the
good
result
has
been
got
with
these
methods. The methods based on edge map
and frequency analysis is used in the
process
of
the
localization
of
the
license
plate,
that
is
to
say,
extracting
the
characteristics of the license plate in
the car images after being checked up for
the edge, and then analyzing and
processing
until the probably area of
license
plate is extracted.
The automated license plate location is
a part of the
image processing
,it’s
also an important part
in the intelligent traffic
system
．
It is the key step in
the
Vehicle
License
Plate
Recognition(LPR).A
method
for
the
recognition
of
images
of
different
backgrounds
and
different
illuminations
is
proposed
in
the
upper
and
lower
borders
are
determined
through
the
gray
variation
regulation of the
character left and right borders are determined
through the black-white variation of
the pixels in every row.
The
first
steps
of
digital
processing
may
include
a
number
of
different
operations
and
are
known
as
image
processing
．
If
the
sensor
has
nonlinear
characteristics,
these
need to be corrected
．
Likewise
，
brightne
ss and contrast of
the
image
may
require
impro
vement
．
Commonly
，<
/p>
too
，
coordinate
transformations are needed to restore
geometrical distortions introduced during
image
formation
．<
/p>
Radiometric
and
geometric
corrections
are
elementary
pixel
processing
operations
．
It
may
be
necessary
to
correct
known
disturbances
in
the
image
，
for
instance
caused
by
a
defocused
optics
，
motion
blur
，
errors
in
the
sensor
，
or
errors
in
the
transmission
of
image
signals
．
We
also
deal
with
reconstruction
techniques
which
are
required
with
many
indirect
imaging
techniques
such
as
tomography that deliver no direct
image.
A
whole
chain
of
processing
steps
is
necessary
to
analyze
and
identify
objects
．
First
，
adequate
filtering
procedures
must
be
applied
in
order
to
distinguish
the
objects
of
interest
from
other
objects
and
the
background
．
Essentially
，
from an
image
（
or several
images
）
，
one or
more feature
images
are
extracted
．
The
basic
tools
for
this
task
are
averaging
and
edge
detection and the
analysis of simple neighborhoods and complex
patterns known
as
texture
in
image
processing
．
An
important
feature
of
an
object
is
also
its
motion
．
Techniques
to
detect
and
determine
motion
are
necessary
．
Then
the
object
has
to
be
separated
from
the
background
．
This
means
that
regions
of
constant features and discontinuities
must be identified
．
This
process leads to a
label
image
．
Now that we know the
exact geometrical shape of the
object
，
we
can
extract further information such as the mean gray
value
，
the area
，
perimeter
，
and other
parameters for the form of the
object[3]
．
These parameters
can be used
to
classify
objects
．
This
is
an
important
step
in
many
applications
of
image
processing
，
as
the
following
examples show
：
In
a
satellite image
showing
an
agricultural
area
，
we
would
like
to
distinguish
fields
with
different
fruits
and
obtain
parameters to estimate their ripeness or to detect
damage by parasites
．
There
are
many
medical
applications
where
the
essential
problem
is
to
detect
pathologi-al changes
．
A
classic example is the analysis of aberrations in
chromosomes
．
Chara
cter recognition in printed and handwritten text
is another
example
which
has
been
studied
since
image
processing
began
and
still
poses
significant
difficulties
．
You
hopefully do more
，
namely try
to understand the meaning of what you
are reading
．
This
is also the final step of image
processing
，
where one aims to
understand the observed
scene
．
We perform this task
more or less unconsciously
whenever
we
use
our
visual
system
．
We
recognize
people
，
we
can
easily
distinguish between the image of a
scientific lab and that of a living
room
，
and
we watch
the traffic to cross a street
safely
．
We all do this
without knowing how
the
visual
system
works
．
For
some
times
now
，
image
processing
and
computer-graphics have been treated as
two different
areas
．
Knowledge in both
areas
has
increased
considerably
and
more
complex
problems
can
now
be
treated
．
Computer
graphics
is
striving
to
achieve
photorealistic
computer-generated
images
of
three-dimensional
scenes
，
while
image
processing
is
trying
to
reconstruct
one
from
an
image
actually
taken
with
a
camera
．
In this
sense
，
image processing
performs the inverse procedure to that
of computer
graphics
．
We start with
knowledge of the shape and features of an
object
—
at the
bottom of Fig. and work upwards until we get a
two-dimensional
image
．
To handle
image processing or computer
graphics
，
we basically have
to
work
from
the
same
knowledge
．
We
need
to
know
the
interaction
between
illumination
and
objects
，
how
a
three-dimensional
scene
is
projected
onto
an
image plane
，
etc
．
There are still
quite a few differences between an image
processing and a
graphics
workstation
．
But
we
can
envisage
that
，
when
the
similarities
and
interrelations
between
computergraphics
and
image
processing
are
better
understood
and
the
proper
hardware
is
developed
，
we
will
see
some
kind
of
general-
purpose
workstation in
the
future
which
can
handle
computer
graphics
as
well
as
image
processing
tasks[5]
．
The
advent
of
multimedia
，
i.
e.
，
the
integration
of
te
xt
，
images
，
sound
，
and
movies
，
will
further
accelerate
the
unification of computer
graphics and image processing.
In
January 1980 Scientific American published a
remarkable image called
Plume2
，
the second
of eight volcanic eruptions detected on the Jovian
moon by
the spacecraft Voyager 1 on 5
March 1979
．
The picture was a
landmark image in
interplanetary
exploration
—
the first time
an erupting volcano had been seen in
space
．
It was also
a triumph for image
processing
．
Satellite imagery and images from
interplanetary explorers have until fairly
recently been the major users of image
processing techniques
，
where
a computer
image
is
numerically
manipulated
to
produce
some
desired
effect-such
as
making a particular
aspect or feature in the image more visible.
Image processing has its roots in photo
reconnaissance in the Second World
War
where
processing
operations
were
optical
and
interpretation
operations
were performed by humans who undertook
such tasks as quantifying the effect
of
bombing raids
．
With the
advent of satellite imagery in the late
1960s
，
much
computer-based work began and the color
composite satellite
images
，
sometimes
startlingly beautiful, have become part
of our visual culture and the perception
of our planet
．
Like
computer
graphics
，
it
was
until
recently
confined
to
research
laboratories which could afford the
expensive image processing computers that
could
cope
with
the substantial
processing
overheads
required to
process
large
numbers
of
high-
resolution
images
．
With
the
advent
of
cheap
powerful
computers and image collection devices
like digital cameras and
scanners
，
we
have
seen
a
migration
of
image
processing
techniques
into
the
public
domain
．
Classical
image
processing
techniques
are
routinely
employed
by