Center pixel depth measurement: read a fixed image point

A depth readout at the image center should answer one question: what valid depth does this specific pixel report? It should not silently search the scene for a nearer surface. This procedure is for applications that display a fixed crosshair, monitor a stationary target, or log a repeatable image location. You will calculate the center from the acquired depth frame, interpret its units and validity, and place the marker correctly when the display uses a different image stream.

1. Define the point and the measured quantity

Separate three operations before changing any code:

For example, a center target might report 1.25 m while an object near the corner reports 0.42 m. Both values can be correct. A minimum-depth search returns the corner object, not the center target.

Also establish what the depth value means. Some streams report axial depth along the camera's optical axis; others report radial distance from a defined camera origin. These quantities differ away from the optical axis. Use the documented definition and label the readout accordingly.

Reading one pixel does not produce a full spatial coordinate. For deprojection and coordinate frames, use the separate image-pixel-to-3D mapping procedure.

2. Calculate the center from the acquired depth frame

Read width and height from the depth frame you will sample, not from a preview window, color image, or requested configuration. A request can differ from the mode actually delivered.

For zero-based pixel coordinates, use this convention:

Here, u is the horizontal coordinate and v is the vertical coordinate. Many array interfaces index rows before columns, so the access order is [v, u]. An SDK accessor may instead accept (u, v); check its signature rather than copying the array convention.

For a 640 × 480 frame:

• Horizontal indices run from 0 through 639.
• Vertical indices run from 0 through 479.
• The selected center pixel is (320, 240).
• The corresponding array access is [240, 320].

An even-sized image has no single pixel exactly at its geometric center. Its geometric center is (319.5, 239.5) in this example. Integer division selects the lower-right pixel among the four central pixels. That is a consistent convention, not a measurement error.

Recalculate after a resolution, crop, or region-of-interest change. A pixel fixed within an output image does not necessarily represent the same physical viewing direction after cropping. The pixel-step alignment cursor guide helps distinguish image coordinates from display movements.

3. Confirm units, validity, and the decoding stage

Do not assume an integer sample is already a distance in millimeters. Depending on the delivered format, it might represent scaled depth, disparity, confidence, or packed data requiring decoding.

First identify the stream and pixel format. If the software cannot identify the depth payload, resolve that before adding a measurement overlay. Follow the missing-depth-stream and pixel-format checks.

For a documented, linearly scaled depth format:

As a hypothetical conversion, suppose a valid sample is 1250 and the documented scale is 0.001 m per raw unit:

These are example values, not a specification for a listed sensor. Obtain the actual scale from the device documentation, stream metadata, or documented API. Do not apply a scale twice when an accessor already returns physical units.

Next, identify invalid readings. Depending on the format, invalidity may appear as a reserved value, a nonfinite floating-point value, or a separate validity or confidence indication. A zero value is invalid only where the format defines it that way.

A suitable interface displays an invalid state rather than a fabricated distance. If you retain the last valid value, mark it as stale and show its age separately.

4. Implement a guarded center sampler

Keep acquisition, decoding, sampling, and rendering as separate stages. The sampling function should receive a retained frame or an owned array whose contents cannot change during access.

The following Python example assumes an array interface with shape, ndim, and [row, column] indexing. It expects an already decoded scalar depth array, a same-sized validity mask derived from documented validity rules, and a positive linear conversion scale.

import math


def center_depth(depth_raw, valid_mask, meters_per_unit):
    if depth_raw.ndim != 2:
        raise ValueError("Expected a two-dimensional depth array")
    if valid_mask.shape != depth_raw.shape:
        raise ValueError("Validity mask and depth shape differ")
    if not math.isfinite(meters_per_unit) or meters_per_unit <= 0:
        raise ValueError("Invalid depth scale")

    height, width = depth_raw.shape
    if width == 0 or height == 0:
        raise ValueError("Empty depth frame")

    u = width // 2
    v = height // 2
    raw_value = float(depth_raw[v, u])

    if not bool(valid_mask[v, u]) or not math.isfinite(raw_value):
        return (u, v), None

    depth_m = raw_value * meters_per_unit
    if not math.isfinite(depth_m) or depth_m <= 0:
        return (u, v), None

    return (u, v), depth_m

This example accepts only positive physical depth. It does not decode packed formats, convert disparity into depth, or convert radial range into axial depth. Adapt those stages to the documented stream definition before calling the sampler.

At the call site, display None as an explicit invalid result. Keep the returned coordinate with the value so that the overlay cannot accidentally use a different location.

Log the frame identifier, timestamp, actual dimensions, coordinate, scale, validity, and result during commissioning. If acquisition uses a background thread, retain the frame through sampling. Dimensions from one frame and pixels from another make the result difficult to diagnose.

5. Place the crosshair in the correct image space

Start by displaying the depth image itself and drawing the marker at the sampled depth coordinate. This removes color registration from the first test. Keep the overlay and value tied to the same acquisition, as described in the single-acquisition overlay workflow.

A resized depth preview needs a display transform. Under a simple edge-aligned resize, a source pixel center maps approximately as follows:

The offsets describe the image's position inside the display area, including letterboxing. Apply the GUI's drawing convention consistently; some APIs locate pixel centers at integer coordinates rather than half-integer coordinates.

Cropping, rotation, and mirroring require their own transformations. A marker that looks centered in the window may still point at the wrong source pixel.

When the background is a color image

Depth and color images can have different dimensions, fields of view, optical centers, and viewpoints. Matching their resolutions or scaling coordinates proportionally does not establish correspondence.

Choose which measurement you actually need:

• Depth-frame center: sample the original depth center, then project that measured point into the color image using calibrated registration.
• Color-frame center: use a documented depth-to-color registration result, then sample its color-center coordinate with the appropriate validity checks.

These operations can return different values. Registration can also leave holes because a surface visible to one camera may be hidden from the other.

Use the intrinsic-parameter conversion guide when cropping or resizing changes calibration coordinates. For moving targets, also verify depth and color exposure timing; spatial calibration cannot correct frames captured at different moments.

6. Verify the result with a controlled scene

Use a static, opaque target that produces reliable depth before testing difficult surfaces. Keep the target comfortably within the documented operating range, and avoid placing the center on an edge.

Follow this acceptance sequence:

1. Fill the center region with a flat target. Confirm that the logged coordinate matches the calculated center.
2. Move the target along the viewing direction. Check that the displayed value changes in the expected direction and units.
3. Introduce a nearer object at a corner without covering the center. The center reading should remain associated with the center target.
4. Move that nearer object across the center. The reading should change only when it occupies the sampled location, allowing for the sensor's filtering behavior.
5. Test an invalid condition. Confirm that the display reports invalid rather than zero distance or an unmarked previous value.
6. Repeat after resizing the display and changing the acquisition mode. Verify both the sample coordinate and overlay position.

For the earlier example, a center value of 1.25 m and a valid corner value of 0.42 m provide a simple separation test. A whole-frame minimum reports 0.42 m; the fixed-center sampler reports 1.25 m.

A single pixel near a boundary may alternate between surfaces or become invalid. If failures cluster on fibers, narrow features, or close objects, use the close-range depth-dropout checks before changing the sampling logic.

7. Confirm suitable depth output before ordering

Browse 3D sensors through the camera finder, but qualify the delivered data interface before selecting hardware. A sensing method alone does not establish that your software can access the required depth image.

The MV-DPS200P-02 is listed as a projected structured-light camera.

The MV-DT01WMU is listed as a ToF sensing camera.

Treat these as sensing approaches to investigate, not as a guarantee of interchangeable outputs. Confirm scalar depth access, coordinate conventions, depth definition, conversion units, invalid-sample reporting, and frame ownership in the supported interface.

If a color overlay is required, also confirm whether color data, calibration, and registration are available for the proposed configuration. Do not assume those features from a product's sensing category.

8. Complete the deployment checklist

Before accepting the readout, check the following:

• Actual frame dimensions: derive the center from the delivered depth frame, not a requested mode.
• Coordinate order: verify column-row coordinates against row-column array indexing.
• Measurement definition: label axial depth or radial range according to the stream documentation.
• Units: apply the documented conversion exactly once.
• Validity: use the format's validity rules and expose missing measurements clearly.
• Frame consistency: sample, log, and render data from the intended acquisition.
• Display transform: account for resizing, padding, cropping, rotation, and mirroring.
• Color correspondence: use calibrated registration rather than an assumed resolution ratio.
• Application meaning: distinguish a fixed sample from a minimum search or neighborhood estimate.

The usual single-pixel answer is wrong when the application really needs a stable surface estimate. A valid-sample median over a 5 × 5 neighborhood may reduce isolated fluctuations, but it samples 25 locations and can cross object boundaries. Label it as a neighborhood statistic and define the minimum valid-sample count. Do not present it as an unchanged center-pixel reading.

For a new installation, start with the camera configuration step. For interface or registration questions, contact the applications team with the required stream format, working distance, target surface, and display arrangement.