Finding Differences in Images with PHP

This article explores a fascinating question: how can we efficiently determine if two images differ significantly? For PHP developers, image resizing with minimal quality loss is a common challenge. This tutorial leverages fundamental mathematical principles to simplify this task.

The solution hinges on applying basic mathematical concepts to bitmap image processing. The code for this tutorial is available at https://www.php.cn/link/47eb3187889a93d645fd86b3ca9ca304.

Key Concepts:

• Utilizing PHP and mathematical principles to detect substantial image changes.
• Employing the Euclidean distance formula for pixel-level difference calculation.
• Creating a third bitmap to visualize these differences.
• Implementing a PHP class to manage image loading, bitmap generation, and comparison.
• Using standard deviation to filter minor variations, enhancing accuracy.
• Identifying and outlining change boundaries for precise difference visualization.

Bitmap Processing:

Images can be viewed as pixel grids with varying color and contrast levels (represented by RGB or HSL values) or as vectors (defined by points and metadata). This tutorial focuses on the simpler bitmap approach. The following code snippet demonstrates bitmap creation:

$image = imagecreatefrompng($path);
$width = imagesx($image);
$height = imagesy($image);

$map = [];

for ($y = 0; $y < $height; $y++) {
    $map[$y] = [];
    for ($x = 0; $x < $width; $x++) {
        $color = imagecolorat($image, $x, $y);
        $map[$y][$x] = [
            "r" => ($color >> 16) & 0xFF,
            "g" => ($color >> 8) & 0xFF,
            "b" => $color & 0xFF
        ];
    }
}

This code iterates through each pixel, extracting RGB values using bit shifting and masking. Each RGB value ranges from 0 to 255 (00000000 to 11111111 in binary).

Euclidean Distance:

Comparing bitmaps involves calculating the distance between corresponding pixels. The Euclidean distance formula is ideal for this three-dimensional (RGB) comparison:

$first = [$red = 100, $green = 125, $blue = 150];
$second = [$red = 125, $green = 150, $blue = 175];

$red = $second[0] - $first[0];
$red *= $red;
$green = $second[1] - $first[1];
$green *= $green;
$blue = $second[2] - $first[2];
$blue *= $blue;

$distance = sqrt($red + $green + $blue); // ≈ 43.30

This formula extends to higher dimensions if needed.

Image Difference Calculation:

A PHP class simplifies image loading, bitmap creation, and difference calculation:

class State { /* ... (Class definition as in the original text) ... */ }

This class uses the Euclidean distance to generate a difference map.

Standard Deviation for Noise Reduction:

To filter out minor variations, standard deviation is applied. This involves calculating the average pixel difference and identifying values within the standard deviation range, which are then treated as insignificant.

Boundary Detection:

A boundary() method identifies the rectangular region encompassing significant changes, providing precise visualization.

Conclusion:

This approach effectively identifies significant image differences. The combination of Euclidean distance, standard deviation filtering, and boundary detection provides a robust solution for various applications, including automated testing and image comparison tasks. Further improvements and alternative methods are welcome.

Frequently Asked Questions (FAQs):

The FAQs section from the original text remains largely unchanged and provides valuable information on PHP image comparison techniques using GD and Imagick, addressing aspects such as image format handling, accuracy, performance optimization, and limitations.

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