Using PHP and OpenCV for Real-Time Camera Image Processing

1. Install required software and drivers

To call a camera from PHP you first need OpenCV and the php‑opencv extension. On Windows you can download the latest OpenCV binaries from the official site and compile/install the php‑opencv plugin from its GitHub repository following the documentation.

1.1 Install OpenCV

Download the appropriate OpenCV package for your OS from https://opencv.org/ and complete the installation.

1.2 Install php‑opencv plugin

The php‑opencv extension provides PHP bindings for OpenCV. Clone the source from https://github.com/opencv/opencv_contrib, compile and install it according to the official guide.

2. Capture camera and display real‑time image

After the software is installed, you can write PHP code that opens the default camera, reads frames, encodes them as BMP, and outputs them as base64‑encoded tags so the browser shows the live video.

<?php
$video = new VideoCapture(0); // Open default camera
while (true) {
    $frame = $video->read(); // Read a frame
    if ($frame !== null) {
        $image = cvimencode(".bmp", $frame); // Encode frame
        echo "<img src=\"data:image/bmp;base64," . base64_encode($image) . "\"/>"; // Display image
    }
    if (waitKey(1) >= 0) { // Exit on any key press
        break;
    }
}
$video->release(); // Release camera resource
?>

The script uses VideoCapture, reads frames in a loop, encodes each frame, echoes an tag, and exits when any key is pressed, releasing the camera resource.

3. Real‑time image processing

Beyond simply displaying frames you can process them, for example performing face detection with OpenCV’s Haar cascade. The code converts each frame to grayscale, applies histogram equalization, detects faces, draws rectangles around them, and then displays the processed image.

<?php
$video = new VideoCapture(0); // Open default camera
$cascade = new CascadeClassifier('haarcascade_frontalface_default.xml'); // Load face model
while (true) {
    $frame = $video->read(); // Read a frame
    if ($frame !== null) {
        $gray = cvcvtColor($frame, cvCOLOR_BGR2GRAY); // Convert to gray
        cvequalizeHist($gray, $gray); // Histogram equalization
        $faces = $cascade->detectMultiScale($gray); // Detect faces
        foreach ($faces as $face) {
            cvectangle($frame, $face, new Scalar(0, 255, 0)); // Draw rectangle
        }
        $image = cvimencode(".bmp", $frame); // Encode frame
        echo "<img src=\"data:image/bmp;base64," . base64_encode($image) . "\"/>"; // Display image
    }
    if (waitKey(1) >= 0) { // Exit on any key press
        break;
    }
}
$video->release(); // Release camera resource
?>

This tutorial provides a basic, entry‑level example of using PHP with OpenCV for real‑time camera access and image processing, which can be extended with more advanced algorithms.