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Field-of-View Calculator

Field-of-View and Why it Matters

An airborne camera’s field-of-view (FOV) represents the ground swath width, while a machine vision camera‘s FOV looking down on a conveyor belt represents the image width across the belt. However, a trade off exists between FOV and spatial resolution. As you increase one, you decrease the other.

In airborne applications, variables such as altitude, desired resolution, and flight speed all come into play. For advanced machine vision applications, variables include speed and width of the inspection line, frame rates, and resolution.

Headwall’s experienced sales engineers can help you understand the variables and tradeoffs so that the solution we provide is perfectly matched to your application!

Headwall’s Nano HP VNIR-SWIR sensor collects 340 spectral bands by 1020 spatial pixels within the visible-to-near-infrared (VNIR) range from 400nm to 1000nm. It is the world’s most popular airborne hyperspectral imager. The MV.C VNIR collects 342 spectral bands by 1024 spatial pixels in the same VNIR range for machine vision applications.

FOV depends on altitude and focal length. This is why Headwall offers a variety of standard lenses from 8mm to 100mm.  Higher altitudes / more height over a conveyor belt usually mean a wider FOV while lower altitudes mean a narrower FOV. Therefore, higher altitudes / more height typically translate into lower resolution.

Similarly, a shorter focal length lens equals a wider FOV while a longer focal length lens equals a narrower FOV. The angular FOV is set by the lens, but the swath width (or linear FOV) depends on the altitude flown or height over your products being inspected.

Headwall’s powerful Field of View Calculator can work for you.

The objective is to optimize height (or altitude), spatial pixel size, and swath width by choosing the best lens for the variables in effect.

Choosing a Lens

Choice of lens matters for Nano HP VNIR (400-1000nm). This table illustrates the relationship between spatial resolution and the acreage you’ll cover. It is very much a trade-off, and these figures do not factor in variances in flying speed.

Please note that other lenses are available for other wavelength ranges and for other applications such as industrial machine vision. 

FOV-table-Nano-HP

Frame Rate and FOV

An objective of planning most remote sensing flights is to achieve square pixels. That is, matching the frame rate of the sensor to the flight speed of the UAV or aircraft. Square pixels require one instantaneous field of view (IFOV) per frame. If the frame rate is too slow, the pixels will not be square.

For machine vision applications, square pixels are not as important. In fact, in many situations having the highest possible speed outweighs having square pixels. Once a defective item or foreign object is detected, simply knowing the location (which is easily calculated square pixels or not) is enough for a robot down the line to perform a removal or sorting operation.

The field of view calculator

Spatial Resolution and FOV

Spatial resolution along the image slit depends on focal plane resolution (pixel pitch and number of pixels) as well as the field of view.

Spatial resolution in the travel direction depends on travel (flight or machine vision target object) speed, slit width (one to three pixels wide, depending on throughput requirements), and detector integration time and/or frame rate.

The Polygon Tool: Flight Planning

There are several factors involved in managing the flight. The first consideration is, “What resolution is required?” The answer to this important question will help determine the lens selection as well as the flying altitude.

Next, “What are the dimensions of the scanning area?” This will help determine the number of flight lines needed. Headwall’s Polygon Tool allows the user to pinpoint areas of data collection, which optimizes the flight parameters with respect to battery life and data storage.

Please note that the Polygon Tool is not designed to manage the flight of the aircraft. It is only provided as an aid to users in defining data collection coordinates.