> For the complete documentation index, see [llms.txt](https://docs.rekor.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rekor.ai/rekor-edge-max-tm/rekor-edge-max-tm-for-alpr/alpr-camera-placement.md).

# ALPR Camera Placement

This question is frequently asked, yet providing a precise answer can be challenging. The accuracy of our LPR system relies heavily on the quality of the input video it receives. If a human observer cannot easily discern the characters on a license plate, the software will encounter similar difficulties. Achieving high accuracy is probable when the camera is properly configured to capture license plates clearly. Conversely, the results may be less accurate if the camera does not capture license plates with sufficient clarity.

To determine if your camera is compatible with our LPR system, we recommend conducting a simple test: freeze a frame from a passing car and attempt to read the license plate number. If this task proves challenging, our LPR system may not perform successfully with your camera. Even when the plate numbers are legible, it's important to note that the camera might not be optimally configured for LPR. While the human brain excels at pattern recognition from visual data, a computer requires a clear and ideal image to operate at its best.

In the image below, the license plate appears legible as "GFP 3054." However, the letters lack sharp contrast, and the blurry shades of gray blend into the plate background and surrounding characters. In such cases, a machine may struggle to read the license plate accurately.

![](/files/536ed17b2d87b1dd146ebaca1a5672be8bdde55b)

The same license plate is much better defined in the following photo, in which the lighting was upgraded and the camera was zoomed in.

![](/files/b10f5c638a96ae341addcecef44a95bde66609be)

The most important factors affecting LPR accuracy are camera placement and video quality. To achieve the highest possible performance for your LPR system, optimize the following variables:

1. Lighting
2. Camera Positioning
3. Pixels on Target
4. Camera Image Settings


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.rekor.ai/rekor-edge-max-tm/rekor-edge-max-tm-for-alpr/alpr-camera-placement.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
