In PHP image processing, the imageconvolution function is a powerful tool for applying custom filter effects.
Emboss effects typically enhance image edges and introduce a simulated light source to create a three-dimensional feel. Below is a common convolution matrix for embossing:
This matrix simulates lighting from the top-left corner, creating a sense of depth. Example implementation:
Shadow effects are commonly used to enhance depth or highlight subjects. The following is a convolution matrix that simulates a shadow by applying blur and slight offset:
This matrix performs a mild blur on the image. To make it more like a shadow, it’s often combined with transparency overlays or layer offsets. Here's how to use it:
imageconvolution offers flexible capabilities for image processing. By designing different convolution matrices, we can achieve a wide range of visual effects. Embossing is ideal for highlighting structural lines in images, while shadow effects help emphasize visual layering and focal points. In practical applications, understanding and combining these basic effects is a crucial step toward advanced image processing.
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How to Use the imageconvolution Function to Create Emboss and Shadow Effects? A Comparative Analysis
2. Emboss Effect Implementation
$embossMatrix = [
[-<span class="hljs-number">2, -1, 0],
[-1, 1, 1],
[ 0, 1, 2]
];
$img = imagecreatefromjpeg('example.jpg');
imageconvolution($img, $embossMatrix, 1, 128);
imagejpeg($img, 'embossed.jpg');
imagedestroy($img);
3. Shadow Effect Implementation
$shadowMatrix = [
[1, 1, 1],
[1, 0, 1],
[1, 1, 1]
];
$img = imagecreatefrompng('logo.png');
imageconvolution($img, $shadowMatrix, 8, 0);
imagepng($img, 'shadowed.png');
imagedestroy($img);
4. Comparison of Emboss and Shadow Effects
Feature
Emboss Effect
Shadow Effect
Main Purpose
Enhance edge relief of the image
Highlight objects and simulate light shadows
Common Use Cases
Icon 3D styling, artistic text effects
UI buttons, layer separation
Visual Style
Simulates stone or metallic surfaces
Soft shadows or dark glows
Technical Approach
Asymmetric convolution matrix + offset
Blur convolution matrix + local offset
5. Summary