ANPR / NPR / LPR technology
Automatic Number Plate Recognition
(ANPR) is the next growth product to take off in the world in fact, it is already beginning to be the
biggest potential earner for installation companies. One problem is that it
crosses technological barriers and the needs of available bandwidth were
conveniently obscured.
On the other hand ANPR technology is
completely within the scope of knowledge of CCTV companies, although there are
a few new terms and technologies to come to grips with. We will start by
considering ANPR for a single lane using a dedicated camera and go on to
discuss some other applications such as multi-lane systems and Town Centre
systems with colour cameras.
Core
Technology
If you scan a document into your PC
and then open it in a word processor you cannot edit or alter it in any way.
This is because it is simply one bitmap made up of thousands of individual
pixels. However there is software available, frequently a freebie with scanners
that can convert these groups of pixels into characters. This is Optical
Character Recognition (OCR), which scans each group of pixels and estimates
whether or not it could be a letter and replaces the pixels with the ASCII*
code for the letter. For instance the ASCII code for the lower case 'a' is
01100001. So, the software scans the whole document and produces a page of
letters exactly the same as though you had typed them in, which can be edited
or manipulated in any way.
(*) American Standard Code
for Information Interchange.
OCR is the fundamental technology
used in ANPR and provides the capability to store and sort data. ANPR cameras
need to be a special type and set up within certain important parameters as
will be described later.
As a vehicle approaches the camera
the software takes a series of 'snapshots' and stores them in a file. When the
number plate is of sufficient size for the OCR software the frame is scanned
and the registration number is converted to ASCII code and held in a list. This
continues for a series of images according to the speed and position of the
vehicle. The list is scanned for similarities and a 'favourite' selected to
retain. The system would typically scan and compare 10-15 images, with 5 being
considered the minimum for high accuracy. Note that this is the principle of
the software we are describing; some systems only take one image at a certain
position.
This then, is the start of the ANPR
capture and is totally dependant on the correct set up of camera, lens,
illumination, angle of view and configuration. Get one wrong and you have a
disappointed customer who won't pay the bill.
At this stage we are concentrating
on the number plate capture but there are many other aspects to be considered
for a completely integrated system, which will be discussed later. Note that
the ANPR capture considered here is monochrome.
The
Behaviour of Reflected Light
To explain some further technology
behind successful ANPR capture we need to look at the behaviour of light. A
basic law of light is that the angle of incidence equals the angle of
reflection. However, number plates in the UK and most other countries have a
special characteristic; they are known as RETRO-REFLECTIVE. The surface is covered
in hundreds of tiny hemispheres which cause light to be reflected back to the
source. This is the same technology used in safety clothing and signs. No
matter from which direction the light is directed, it always reflects back and
makes them very visible.
The
Application of Infrared Illumination to ANPR
If a standard colour or monochrome
camera was focused to read number plates it would have to contend with a huge
variety of lighting conditions, daytime, night-time, sunlight, backlight,
headlights, and so on. One configuration simply would not cope with all
conditions, so there is a need to provide a constant level and direction of
illumination irrespective of any other conditions. And so we come to the
development of special cameras for continuous capture of number plate data.
The camera must be sensitive to the
infrared part of the spectrum, to at least 850 nanometres. Then it must be
fitted with a filter to restrict the visible part of the spectrum. The lens
would have a manual iris set fully open and the shutter speed set to 1/1000th
second. Finally an infrared source must be fitted adjacent to the camera.
Therefore, taking advantage of the
retro-reflective characteristics of number plates, the illumination from the
illuminator will be reflected directly back to the camera. Thus only infrared
light will be seen without any visible light or other reflections or
refractions. The picture will of course be black with no detail except for the
number plate. The OCR software then takes care of converting the image to
usable code.
Note that this is the sort of image
on the monitor both day and night.
Cameras
and Lenses
This then is the core of ANPR
technology, but there are many other factors to be considered. The first of
these are the selection of lens and the distance to view the vehicle. The size
of a UK
license plate on cars and commercial vehicles is approximately 510mm long x
110mm high. Motorcycles are different being approximately 255 x 200. However
more significantly, the minimum height of the letters must be 79mm. The current
UK
font is Charles Wright, although there are some illegal formats seen. The size
of the number plate and the actual characters will need to be of a certain size
when seen by the camera for the OCR software to function. One line of thought
is that the number plate should be 18% of the scene width; I prefer to consider
the vertical height of the characters, which from previous research should be
3% minimum for a 400 line camera. This in fact equates very closely to the 18%
screen width but is more logical when considering different shapes of number
plates. (For instance when a car plate is 18% of the screen a motorcycle plate
would only be 7 %.) Also note that motorcycles currently do not have to
carry a front number plate, but this could change in the future.
This provides the first convenient
way to calculate the lens angle. For 79mm high characters the scene height
needs to be 2633mm. (79 being 3% of 2633). Therefore using a scene height of
2.633M and the known distance, it is a simple matter to calculate the lens
angle and thus the focal length. At this stage the height of the camera has not
been considered but would not make much difference for normal combinations of
distance and camera heights. (See further notes at the end).The following table
shows the lens angle for various distances and a scene height of 2.633M.
Distance to target
|
5M
|
10
|
15
|
20
|
25
|
30
|
35
|
40
|
45
|
50
|
Lens angle
|
29.5°
|
15°
|
10°
|
7.5°
|
6°
|
5°
|
4.3°
|
3.8°
|
3.4°
|
3°
|
Focal length 2/3"
|
13mm
|
25
|
38
|
50
|
63
|
76
|
88
|
99
|
111
|
126
|
Focal length ½"
|
9mm
|
18
|
27
|
37
|
46
|
55
|
64
|
72
|
81
|
92
|
Focal length 1/3"
|
7mm
|
14
|
21
|
27
|
34
|
41
|
48
|
54
|
61
|
69
|
Focal length ¼"
|
5mm
|
10
|
15
|
20
|
25
|
30
|
35
|
40
|
45
|
51
|
From this table you can find the
nearest lens focal length for the sensor size. Where the focal length falls
between two available lenses, a vari-focal lens can solve the issue.
In instances where the camera height
is large compared to the horizontal distance the number plate can produce the
effect of being rotated vertically. It is important to check with the software
provider if this is acceptable.
Vehicle Speed and Capture Rate
Another very important consideration
is the speed of the vehicles to be monitored and the width of the area to be
covered. There are again two important interrelated elements connected with
vehicle speed. One is the rate of the image grabber software the other is the
speed of the processor. With modern processors the latter can no be ignored.
Consider a vehicle travelling at 30
MPH, this equates to 13.4 Metres in one second. A UK camera produces 50 fields per
second and the shutter speed is usually 1/50th second. In 1/50th second the
vehicle would travel 0.27 Metres (268mm). This would cause a blurred image and
problems with the OCR translation. For this reason the shutter speed should be
set to 1/1000th second, in which case the vehicle would travel only 0.013
Metres (13.4mm). The same reasoning applies when trying to capture moving
images with a 35mm camera. This is slightly less important when looking head on
at a vehicle but becomes increasingly important when the vehicle is at an angle
approaching the camera.
Where the camera is positioned other
than directly in the line of the approaching vehicle the ANPR provider must be
consulted. Many systems will not function with more than more 1 or 2 degrees of
horizontal skew or vertical rotation.
The positioning of the camera is a
most important consideration for satisfactory operation of an ANPR system. This
can vary the percentage of recognitions to number of vehicles from 30% or 40%
to near on 100%. The camera location depends on several factors, such as:
Single camera covering a barrier entrance
Probably the best position
is for a camera and illuminator in a 1M high bollard viewing directly at the
approaching vehicle.
Single
camera covering one lane
This could be a pole
mounted unit about from 18M to 30M from the vehicle.
Single or
multiple cameras covering multiple lanes
This
is a special application requiring input from the ANPR provider.
The first thing to address
is the shutter speed if it is adjustable. The best would be if the speed can be
set remotely, if not each camera needs to be visited and the speed set
manually. The optimum setting is to 1/1000th. Alternative settings may be
1/250th for traffic up to 5 MPH and 1/500th for traffic up to 40 MPH. Note that
all these settings will affect the low-light capability of the cameras and a
compromise may be required.
Another consideration is
that the camera positions and heights would not be at the optimum for ANPR.
Particular attention must be paid to the angles of skew and rotation and a
guaranty obtained that an acceptable percentage of recognitions will be
achieved.
Cameras on
motorway bridges
Again a special
application requiring input from the provider.
Congestion charging cameras
This application requires
input from the ANPR provider and local authority before even starting to think
of a specification.
Cameras in
Police vehicles
These are normally colour
cameras mounted on a swivel mount and can view images to the front or either
side of the vehicle. This is another special application requiring input from
the provider.
It is often necessary to
have a conventional colour image of the vehicle especially where prosecution or
congestion charging is the application. This would be a separate colour camera
mounted alongside or just below the ANPR camera. Saving the overview image is
triggered by the ANPR camera registering a number plate. This then adds a
colour image to the same file for future reference. It is generally a false
economy to attempt to combine the number plate recognition and overview using a
single camera for 24/7 operation.
Multi-national
number plates
There are thousands
overseas vehicles on the roads today, many of them with symbols and other
labels incorporated into the plate. The ANPR system must be capable of reading
all of these. The software should have a built-in list of such plate styles.
Just capturing number
plates and storing them is not much use by itself. The screenshot below shows
an ANPR example review screen. The associated database should be able to
provide much more information.
Searching should possible on several
fields:
- Full plate.
- Part plate.
- Time.
- Date.
- Category.
- Notes added to image file.
Further functions could be:
- Counting vehicles in and out of premises, leaving a
list of all vehicles on site.
- The length of time a vehicle is on site.
- Vehicle speed (from two cameras).
- Employee names can be associated with number plates and
access allowed or denied to certain areas.
Example
flow diagram for ANPR system
Vehicle
speeds and distances
The following table shows distances
travelled for different speeds. This will give some indication to the number of
images that be captured. From this table it can be seen that fof a vehicle
travelling at 50MPH at 1/50th exposure it will travel nearly half a metre
resulting in a blurred image. Compared to only 22mm at 1/1000th exposure.
Image
grabbers
These are sometimes known as frame
grabbers or field grabbers or stores. In reality they all store images or
single fields.
This is a particular area where you
really pay for what you get. The main criterion is the speed at which images
can be captured. For instance Video for Windows can only store about 8 images
per second which is only suitable for very slow moving or stationary traffic.
ANPR
is the generic term generally used in the UK but other terms are common in
other parts of the world. Such as; NPR (Number Plate Recognition), LPR (License
Plate Recognition). To know more please click on License Plate Recognition 21st.
The key
elements that go into the solution are a competent IP camera and an analytic
software that converts images to computer data. It is important that the camera
is capable of capturing excellent quality images, as the analytics software is
heavily dependent on this.
Genetec AutoVu SharpX ALPR camera
SharpX is
an IP-based automatic license plate recognition (ALPR) camera designed for
demanding mobile and fixed applications. With its small form factor, high
resolution and integrated illumination, the SharpX captures more license plates
in a variety of conditions and at high speeds. Supporting up to four cameras
connected to a single external processing unit.
IntelliVision License Plate Recognizer
IntelliVision’s License
Plate Recognizer is a deep learning and AI-based license plate detection,
recognition and search solution with an accuracy as high as 98%. It takes into
account variables such as movement and high speeds which are natural to the
environment of vehicle monitoring. Real-time searching can also be performed on
each plate detected, comparing the information gathered with a stored database
of license plates.
VIVOTEK IP816A-LPC-v2 Kit
IP816A-LPC-v2
Kit represents a total solution for license plate capture (LPC)
applications by leveraging the top-tier image quality and traffic monitoring
ability of the IP816A-LPC box camera. The CaMate IR illuminator utilizing CVA
Tech provides adjustable beam angles for different distances. A headlight
filter is implemented to reduce instances of glare from direct headlight
contact. The kit delivers clear license plate images for reliable recognition,
in both the sunniest days and the darkest nights. Empowered with VIVOTEK Scene
Mode, which provides different exposure levels to avoid overexposure in some
lighting conditions, the kit can capture clear plate images from the vehicles
moving at speeds of up to 85 mph (140 km/hr).
PlateSmart ARES Viewer
ARES Viewer is
a stand-alone application with an easy-to-use interface that allows widespread
and quick access to vehicle recognition data and alerts in real time. It
communicates vital information and allows users to view real-time data from
anywhere, at any time, through a VPN connection to their network. ARES Viewer
safely locks away the administrative power of the command center and makes
plate and notification information available for each licensed user.
Luxriot license plate recognition software
Luxriot LPR is
an automatic license plate recognition application that is designed to work
with the Luxriot VMS Server. This application accommodates customers with the
specific need to detect, recognize and register motor vehicle license plates,
and then stores recognized license plates and snapshots on local or central
database. Luxriot LPR, which supports a multitude of IP and analog cameras, is
ideal for vehicle access control applications as well as for traffic control
and enforcement applications.
কলকাতার
বেশ কিছু জায়গায় বসেছে
অটোম্যাটিক নম্বর প্লেট রিকগনিশন (এ.এন.পি.আর.) ক্যামেরা।এই ক্যামেরা
এমন বি়জ্ঞানসম্মত ভাবে বসানো হয়েছে
যে নম্বর ছাড়াও গাড়িতে কারা বসে রয়েছেন,
তাঁদের চেহারা এবং গতিবিধিও পরিষ্কার
ধরা পড়ছে। অপরাধ দমনে যাহা গুরুত্বপূর্ণ
ভূমিকা পালন করে চলেছে
| জেনে নেওয়া যাক কি এই
এ.এন.পি.আর.
ক্যামেরা (ANPR / LPR Camera
) ?
ক্যামেরাটির
বিশেষত্ব হল, এখানে যে
কোনও গাড়ির নম্বর স্বয়ংক্রিয় ভাবে ধরা পড়বে।
এমনকি ঘণ্টায় ৫০-৬০ কিলোমিটার
গতিবেগে চলা কোনও গাড়ির
নম্বর প্লেটের ছবিও স্পষ্ট ভাবে
নিতে পারে উচ্চ ক্ষমতাসম্পন্ন
এএনপিআর ক্যামেরা। এই ক্যামেরা মূলত
অপটিক্যাল ক্যারেক্টার রিকগনিশন প্রযুক্তিতে কাজ করে। অপ্টিকাল
ক্যারেক্টার রেকগনিশন হাতে লেখা বা
টাইপরাইটারে টাইপকৃত লেখার ছবিকে (সাধারণত স্ক্যানার দিয়ে স্ক্যান করা) কম্পিউটারে সম্পাদনাযোগ্য
লেখায় অনূদিত করার যান্ত্রিক বা
ইলেকট্রনিক পদ্ধতিকে বুঝায়। ক্যামেরা টি একটি উচ্চ
ক্ষমতা সম্পন্ন সার্ভার সফটওয়্যার এর সাথে যুক্ত
করা হয়, যাহা একটি
ডাটাবেস তৈরী করে, ওই
ডাটাবেস এ গাড়ির নম্বর
সহ স্থান-কাল-পাত্র জমা
হয় । প্রয়োজন মতো
সেই ডাটাবেস থেকে প্রয়োজনীয় তথ্য
বের করে নেওয়া যেতে
পারে।
গত ০৮ সেপ্টেম্বর, ২০১৭
তে ১২ বছরের মেয়ের
ব্রেন টিউমার অপারেশনের জন্য ভারতে এসেছিলেন বাংলাদেশের
নাগরিক মহম্মদ নুরউদ্দিন আহমেদ। সপরিবারে বিমানবন্দর থেকে ট্যাক্সিতে করে
হাওড়া যান তিনি। ট্রেন
ধরে চেন্নাই যাওয়ার কথা ছিল। কিন্তু
হঠাৎই খেয়াল পড়ে, একটি ব্যাগ ফেলে
এসেছেন ট্যাক্সিতে। ওই ব্যাগেই ছিল
টাকাপয়সা, জরুরি কাগজপত্র। প্রথমে হাওড়া স্টেশন চত্বরের সিসিটিভি ফুটেজ খতিয়ে দেখে পুলিশ। অটোমেটিক
নম্বর প্লেট রিকগনিশন বা ANPR ক্যামেরার মাধ্যমে উদ্ধার হয় ট্যাক্সির নম্বর।
খোঁজ মেলে ট্যাক্সি মালিকের।
উদ্ধার হয় ব্যাগ।
তাছাড়া
এই ক্যামেরা উচ্চ আলোক এর
মধ্যেও বস্তু / চেহেরা চিনতে সখ্যম। ক্যামেরা তে থাকে এইচএলসি
(হাই লাইট কমপেনসেশন) প্রযুক্তি,
ঠিক যেখানে আলোক উৎস সেখানে
ব্রাইটনেস পরিবর্তনের মাধ্যমে একটি কালো বিম্ব
তৈরী করে নিজের পরিবর্তনশীল
লেন্স এবং ইনফ্রারেড সেনসর
মাধ্যমে পূর্ণ ছবিকে দৃশ্যমান করে, যাহা আমাদের
চোখ হয়তো পারেনা।
উচ্চ
প্রযুক্তির ক্যামেরা বসানো বড়ো কথা নয়,
বড়ো কথা হলো
১. পরিমিত রক্ষণাবেক্ষণ, দেখা গেছে রক্ষণাবেক্ষণ
এর অভাবে অনেক দামি ইলেকট্রনিক
দ্রব্য নষ্ট হয়ে যায়।
২. সঠিক ভাবে নিরীক্ষণ
- সফটওয়্যার এ ঠিকমতো তথ্য
সংরক্ষণ হচ্ছেকিনা এবং ক্যামেরা সঠিক
দিকে তাকিয়ে
আছেকিনা, সেটা প্রতিনিয়ত দেখা
উচিত । তাছাড়া নিয়ম
করে সংরক্ষিত তথ্য নিয়মিত ভাবে
খুঁটিয়ে দেখা অত্যন্ত জরুরি।
৩. প্রচার - একটি অন্ত্যন্ত গুরুত্বপূর্ণ
অধ্যায়, সকলের জ্ঞাত হওয়া উচিত এই
পরিসরে ক্যামেরা বর্তমান, রাস্তায় সুরখ্যা লাইন পারকরলেই ক্যামেরা
তে ধরা পড়বে, তাহার
জন্য মোটা অংকের জরিমানা
হতে পারে.
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