ANPR / NPR / LPR technology

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.

Camera Positioning

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.

Overview cameras

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.

The ANPR database

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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DRI in Video Surveillance

DRI in Video Surveillance

Wish you a very happy new year 2018. In today’s competitive environment, having new customers constantly is one of the keys of success. To make professional quotes with proper sketches, realistic test objects, 3D images, mock ups etc, which leave a lasting impression on your clients.

When you are answering queries related to your product, you can quickly glance through the details while your client is on call.

DRI stands for Detection, Recognition and Identification in video surveillance. DRI ranges, expressed in meters, km (or miles), can be found in the specification table of infrared camera brochures. In order to select the right sensor meeting the application requirements, these DRI ranges have to be, first, perfectly defined, but also assessed with regards to globally adopted industrial standards.

DRI Definition

The terms “Detection”, “Recognition” and “Identification” were defined as follow:

• Detection: ability to distinguish an object from the background
• Recognition: ability to classify the object class (animal, human, vehicle, boat …)
• Identification: ability to describe the object in details (a man with a hat, a deer, a Jeep …)

The following pictures illustrate these definitions:

    Left image: Detection – At several kms, 2 targets are detected out of the background 

    Center image: Recognition - a human is walking along the fence 

    Right image: Identification – 2 males with trousers and jackets are identified – one is smoking.

We detect an object when it enters the field of view. Detection means we are aware that an object (or person) now exists where previously it was not seen. Usually, this is due to movement of the object into the field of view of the surveillance camera. Detection simply means we are aware of the object, but have too little details to recognize or identify the object.

As the object moves closer, we may recognize the object from characteristics previously encountered. For example, aircraft recognition is taught to military ground troops and airmen. All aircraft have wings, engines, a fuselage, and tail assembly. They differ in size, shape, number, and position to each other. A particular model of aircraft can be recognized by recalling these characteristics from pictures, drawings or past detailed observations.

Identification is the process where sufficient details are available to uniquely discern a person or object that is previously unknown. Identification requires sufficient detail to accurately describe or recall the characteristics of the subject at a later time. For example, a mug shot (booking photograph) is taken following the arrest of a subject as a means of photographing (recording) sufficient details for later identification by a victim or witness. In video surveillance terms, sufficient detail is calibrated in pixels per foot of the area recorded by the camera.

DRI Ranges

“A picture is worth a thousand words” goes the old and equally wise saying. It is true that most human beings learn much quicker when aided by visuals rather than pure text as that is more in tune with the human psychology of learning.

So instead of remembering commands and functions you will easily remember that yellow color indicates areas where it is possible to recognize people, red color indicates areas suitable for people identification, green areas for detection and so forth.

To put this in perspective, sensors have a resolution of 640×480 which is over 300,000 pixels.
Human “detection” only requires 3.6 of those pixels and “identification” only requires 230 pixels, which is an extraordinarily small amount on the screen that can easily go unnoticed by the human eye. In fact, if this page were the size of your video feed, the area required for a human detection rating is about equivalent to a lowercase letter “i” in this text. The amount of detail visible at the detection, recognition and identification distances is not as high as one might expect, as can be seen in the chart below.

Another thing that is often not mentioned is that these ratings are based on what is termed “ideal conditions” which rarely happen in the real world. The average environmental application will get 25% less than the distance that the thermal camera is rated for and in extreme conditions can be less than 10% of the rated distance.

Based on SR-100 & SR-100P by FLIR the approximate DRI (Detection, Recognition and Identification) range for a vehicle and a human target is listed in Tables 1 & 2.

Lens	Detection	Recognition	Identification
100mm	4.4km	1.1km	580m

Table 1: DRI range for Vehicle with 2.3m critical dimension using a Thermal Security Camera with 38 micron pitch detector

Lens	Detection	Recognition	Identification
100mm	1.6km	400m	200m

Table 2: DRI range for Human Target using a Thermal Security Camera with 38 micron pitch detector

Assumptions:  50% probability of achieving objective at the specified distance given a   2-degree temperature difference and 0.85/km atmospheric attenuation factor.  Actual range may vary depending on camera setup, user experience, environmental conditions, and type of monitor or display used.

Each & every Camera has this DRI ranges, before preparing project oriented ppt, do confirm the ranges & show in a slide with sketch.

Artical publish at safe secure magazine January 2018 issue.

Warrior 2.0 26BF2 is a 1080P 2MP Fixed Lens Mini Bullet Camera

Detect: 100 ft
Recognize: 50 ft
Identify: 25 ft

Laser 2.0 - 26ZV-LIR is a 2MP (1080P) IP PTZ Camera with 33x Optical Zoom & Laser Infrared camera and Spotlight 2.0 - 26ZV-W is a 2MP (1080P) IP PTZ Camera with 22x Optical Zoom & Full Spectrum Light Camera

Detect: 950 ft
Recognize: 875 ft
Identify: 750 ft

Lookout 2.0 - 26ZV is a 2MP (1080P) IP PTZ Camera with 30x Optical Zoom Camera

Detect: 1000 ft
Recognize: 900 ft
Identify: 800 ft

Judge 8.0 - 26DV8 is a 4K (8MP - 4x1080P) Multi-Purpose Lens Dome Camera with Motorized Zoom and IK10 Camera and Gladiator 8.0 - 26BV8 is a 4K (8MP - 4x1080P) Multi-Purpose Lens Bullet Camera with Motorized Zoom and P-Iris Camera

Detect: up to 200 ft
Recognize: up to 150 ft
Identify: up to 100 ft

Deputy 4.0 - 26DF4 - 4MP (2x1080P) Fixed Wide Angle Lens Turret Dome Camera

Detect: 115 ft
Recognize: 50 ft
Identify: 35 ft

Archer 2.0 - 26BV2-L - 2MP Long Range, Low Light Bullet Camera with Motorized Zoom and Focus

Detect: up to 450 ft
Recognize: up to 350 ft
Identify: up to 300 ft

Warrior 4.0 - 26BF4 is a 4MP (2x1080P) Fixed Lens Mini Bullet Camera

Detect: 150 ft

Recognize: 75 ft
Identify: 50 ft

Port Forwarding on a Netcomm 3G Broadband Router

Port Forwarding on a Netcomm 3G Broadband Router 3G15Wn for Camera Online

This guide will walk you through the steps of port forwarding on the Netcomm 3G Broadband router 3G15Wn (Firmware L411-402NVM-C01_R10)

1) Open up your favorite browser and go to the router’s default gateway address.

 http://192.168.1.1 (Default Address)

2) Log in to the router.

Default Username: admin

Default password: admin

3) Once you have logged into your router go to the “Advanced” tab hover over “NAT” then click “Port Forwarding”.

4) Click on “Add” ad the bottom of the page.

5) Be sure to select the radio button “Custom Service” and choose a name for the service (small description eg. web, camera, xbox, etc..). “Server IP Address” is the Internal IP address that you want the port to be open on. Be sure you have “Protocol” set to “TCP/UDP” and “External Port” is the port you wish to open, “Internal Port” is the port leading to the machine on your home network. Apply/Save.

Once you save the settings you should now be able to test your port at www.portchecktool.com. Please keep in mind your ISP (Internet Service Provider) can be blocking certain ports such as port 80, 25 and 21. You can call and ask if they are. If you are still not able to see the ports check your firewall and anti-virus software on your computer.

An example configuration, you have a web cam that has the IP address 192.168.1.100 and it runs on port 80. You want to be able to access this camera from outside your network on port 8080. You would enter the below values into port forwarding page.

Custom Service = Small Description

Server IP Address = 192.168.1.100

Protocol = TCP/UDP

External Port = 8080

Internal Port = 80

Then to view the camera you would use your No-IP host of “somehost.no-ip.com” like this: http://somehost.no-ip.com:8080 to reach the webcam.

Port Forward Troubleshooting

If you are having problems with a port forward, try the following.

1. If you did not exactly follow the How can I forward ports with pfSense? guide, delete anything you have tried, and start from scratch with those instructions.

2. Port forwards do not work internally unless you enable reflection. Always test port forwards from outside your network.

3. If you're still having problems, edit the firewall rule that passes traffic for the NAT entry, and enable logging. Save and Apply Changes. Then try to access it again from the outside. Check your firewall logs to see if the traffic shows as being permitted or denied.

4. Use tcpdump to see what's happening on the wire. This is the best means of finding the problem, but requires the most networking expertise. Start with the WAN interface, and use a filter for the appropriate protocol and port. Attempt to access from outside your network and see if it shows up. If not, your ISP may be blocking the traffic, or for Virtual IPs, you may have an incorrect configuration. If you do see the traffic on the WAN interface, switch to the inside interface and perform a similar capture. If the traffic is not leaving the inside interface, you have a NAT or firewall rule configuration problem. If it is leaving the interface, and no traffic is coming back from the destination machine, its default gateway may be missing or incorrect, or it may not be listening on that port. For certain types of traffic you may see return traffic indicating the host is not listening on that port. For TCP, this would be a TCP RST. For UDP, it may be an ICMP Unreachable message.

Common Problems

1. NAT and firewall rules not correctly added (see How can I forward ports with pfSense?). Hint: You probably do NOT want to set a source port.

2. Firewall enabled on client machine.

3. Client machine is not using pfSense as its default gateway.

4. Client machine not actually listening on the port being forwarded.

5. ISP or something upstream of pfSense is blocking the port being forwarded

6. Trying to test from inside your network, need to test from an outside machine.

7. Incorrect or missing Virtual IP configuration for additional public IP addresses.

8. The pfSense router is not the border router. If there is something else between pfSense and your ISP, you must also replicate port forwards and associated rules there.

9. Forwarding ports to a server behind a Captive Portal. You must add an IP bypass both to and from the server's IP in order for a port forward to work behind a Captive Portal.

10. If this is on a WAN that is not your default gateway, make sure there is a gateway chosen on this WAN interface, or the firewall rules for the port forward would not reply back via the correct gateway.

11. If this is on a WAN that is not your default gateway, ensure the traffic for the port forward is NOT passed in via Floating Rules or an Interface Group. Only rules present on the WAN's interface tab under Firewall Rules will have the reply-to keyword to ensure the traffic responds properly via the expected gateway.

12. If this is on a WAN that is not your default gateway, make sure the firewall rule(s) allowing the traffic in do not have the box checked to disable reply-to.

13. If this is on a WAN that is not your default gateway, make sure the master reply-to disable switch is not checked under System > Advanced, on the Firewall/NAT tab.

14. WAN rules should NOT have a gateway set, so make sure that the rules for the port forward do NOT have a gateway configured on the actual rule.

Remote View Security Camera without Internet Access

Remote View Security Camera without Internet Access

Recently, I spoke to a business owner of a farm who wanted to setup IP security cameras in his barn (a large building on a farm) to keep an eye on his Garden. The farmer wanted to watch live video of the Garden from his house (which is located about 400 feet away from the barn). He also wanted to monitor his cameras when he was away from the farm using his mobile phone. The problem is that the barn does not have an Internet connection.

What is the wireless bridge?
Another option is using a wireless bridge. A wireless bridge connects two wired networks together over Wi-Fi. The wireless bridge acts as a client, logging in to the primary router and getting an Internet connection, which it passes on to the devices connected to its LAN Jacks.

How do you bridge two wireless routers?
1. Determine if your equipment is compatible. ...
2. Place both routers near your computer. ...
3. Set up your primary router. ...
4. Open the configuration page on the secondary router. ...
5. Enable Bridge Mode. ...
6. Specify the secondary router's IP address. ...
7. Enter a unique SSID. ...
8. Place the secondary router.

Using a Long Range Wireless Bridge with Cameras

The above picture provides an overview of how to use a long range wireless bridge to network two buildings (one with and one without Internet access) so that live video from an IP Camera can be remotely viewed from over the Internet. The building on the left represents the farmer’s barn (no internet access, but has power) and the building on the right represents the house. This particular barn was built to be very weatherproof and it is located in an area where there is very little moisture. For areas with more moisture or if the camera is going to directly exposed to more harsh weather elements, I would recommend an outdoor weatherproof camera.

Important note: long range wireless systems require a direct line of sight between the transmitting and receiving antennas. There can be no objects such as buildings and trees that obstruct the view between antennas.

Here is how the system work Long rang wireless systems, include a transmitter and receiver antennas.

1. Mount the transmitter of the wireless system on the outside of the building that does not have an Internet connection. In this case, the horse barn.
2. Drill a hole through the exterior wall to feed the power cable and a CAT-5 cable inside the barn.
3. Mount the camera and connect it to the wireless transmitter using the CAT-5 cable.
4. Connect the power supplies of the camera and WIFI transmitter to a power outlet.
5. Mount the wireless receiver on the house.
6. Drill a hole in the exterior wall for the CAT-5 and power cable for the receiver antenna.
7. Connect the CAT-5 cable to your network router.
8. Connect the power supply of the receiver antenna to a power outlet.
9. The transmitter / receiver pair are configured to form a wireless bridge over WIFI. They can be configured to only connect to each other so there is no interference from other WIFI equipment. The purpose of the wireless bridge is for the camera to communicate with the home network. The home network is connected to a high speed Internet connection such as cable or DSL.
10. Port forwarding is configured on the router so that the IP camera can be accessed from remotely over the Internet.
11. The live video from the camera in the horse stall can now be accessed from anywhere in the world from a web browser. You can require a user id and password for access. The camera can be accessed from Mac, Windows, Android, and iOS.

Some video servers and IP cameras support remote access from a web browser that works for Windows and Mac PCs.

More Video Surveillance Uses for Wireless Bridges

In addition to this single IP camera system explained above, here are some additional ways to use long range wireless systems with multiple security cameras.

Multiple IP Cameras

You can connect multiple IP cameras to a network switch in the building with no Internet access, then connect the switch to the wireless transmitter antenna. Now all of the cameras are connected to the network in the building with Internet access. All cameras can be made accessible over the Internet by setting up port forwarding for each of them.

CCTV Cameras Connected to DVR

You can use a wireless system with CCTV cameras if you have a DVR that is network-able. Here is how this works. The CCTV cameras are hard wired to a DVR using coax cable. The DVR is connected to the wireless transmitter with CAT-5 cable. Now the DVR is available on the network and can be controlled remotely using apps for iPhone, Android, Mac, and Windows. Users can view all cameras that are connected to the DVR.