DORI and Pixel Density at Distance: The Complete CCTV Design Guide
Resolution alone is a meaningless surveillance specification. A 4K camera can fail to identify a subject at 12 metres while a lower-resolution unit succeeds — the difference is governed entirely by pixel density at distance, written PD(d). This guide derives the PD(d) and field-of-view equations from first principles, maps them to the four DORI tiers defined in IEC 62676-4, and shows how to specify the exact lens needed to satisfy any tier at any range.
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1. The governing standard: IEC/EN 62676-4 and the DORI model
DORI — Detection, Observation, Recognition, Identification — is the framework defined in IEC 62676-4 (and BS EN 62676-4) for stating, objectively, what a camera image is good enough to do at a given distance. Each tier corresponds to a minimum pixel density across the target, expressed in pixels per metre (px/m).
| Tier | Minimum pixel density | What it permits |
|---|---|---|
| Detection | 25 px/m | A person is present in the scene |
| Observation | 63 px/m | Some characteristic detail, clothing, action |
| Recognition | 125 px/m | Recognise a known individual with high certainty |
| Identification | 250 px/m | Establish identity beyond reasonable doubt |
Why "1080p" tells you nothing on its own
A camera's resolution only matters relative to how wide a scene those pixels are spread across at the target distance. The same 1920-pixel-wide sensor delivers Identification-grade density at 4 m and barely Detection at 40 m. The specification that matters is always px/m at the distance you care about.
2. Deriving pixel density at distance, PD(d)
2.1 The scene-width equation
The horizontal width of the scene a camera sees at distance d is set by its horizontal field of view (HFOV):
2.2 The core formula
Pixel density is simply the horizontal pixel count spread across that width:
2.3 Worked example
Take a sensor with H_res = 1920 px, a lens giving HFOV = 90°, and a target at d = 15 m. The scene width is W = 2 · 15 · tan(45°) = 30 m, so PD(15) = 1920 / 30 = 64 px/m — just past the Observation tier (63 px/m), but far short of Recognition. To recognise a face here you would need a narrower lens or higher resolution.
3. The lens–sensor relationship behind HFOV
3.1 Focal length is the real lever
HFOV is fixed by sensor width and focal length:
3.2 Sensor format matters
The same focal length produces a different HFOV on a 1/2.8" sensor than on a 1/1.8" sensor, because the physical sensor width differs. Always pair a focal length with its sensor format before trusting a coverage figure.
3.3 Inverting the problem
In practice you work backwards: fix the px/m you need and the distance, solve for the required HFOV, then for the focal length. The CCTV Design Tool performs this calculation from the configured camera resolution, sensor, and lens data, then renders the resulting DORI bands on a calibrated plan.
4. From pixel density to maximum effective range
Rearranging the core formula gives the maximum distance at which a chosen DORI tier (target density PDt) is met:
Real range is shorter than this nominal figure: edge-of-frame lens distortion, low light, IR cut-in, compression artefacts, and motion blur all erode usable density. Treat d_max as a ceiling, not a guarantee, and design with margin.
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5. Applying PD(d) in real layout engineering
Zone your site into Detection, Recognition, and Identification bands — an entrance lobby needs Identification (250 px/m) at the door line, while a perimeter only needs Detection. Place each camera so its tier band lands exactly where the requirement falls, validate the layout against your floor plan, and export an auditable report. For number-plate work, the same model applies: licence-plate Recognition (ANPR/LPR) requires roughly 250 px/m across the plate, scored per vehicle approach angle.