PHP, detecting watermarked images?

Question

I have a library of like 1 million images, and roughly half of these are watermarked with the same, half transparent watermark in the same spot.

Where do I begin, detecting the images with the watermarks? Is there some standard tools for this purpose?

Answer 1

If according to your question, you just want to detect the images that are watermarked, you can use the following algorithm:

• Extract a sample of the watermarking image Scan the watermark image
• pixel by pixel and store the first pixels in an array. Scan each
• image pixel by pixel and store in an array. Whenever a row matrix
• from the image being scanned contains elements of the array in the
• same order, it's most likely a match.

The code could be something like this:

$no_of_pixels = what_you_got;
$matched = 0;
$thumbpixels = array();
$wmark = imagecreatefrompng("watermark.png");
list($width, $height) =  getimagesize("watermark.png");
$tesimage = imagecreatefrompng("test.png");
for($h = 0; $h < $height; $h++){    
    for($w = 0; $w < $width; $w++){
        if(imagecolorsforindex($testimage, imagecolorat($testimage, $w, $h)) == $thumbpixels[0]){
            while($thumbpixels[$i++] === imagecolorsforindex($tesimage, imagecolorat($wmark, $w, $h)) && $no_of_pixels != $matched){
                $matched++;
            }
            if($matched == $no_of_pixels) echo "Voila, we found it!";
        }
    }
}

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EDIT

Just seeing your thumbnail example. If you just want to detect text, you can try tesseract-ocr or PhpOCR.

You may also consider PHPSane

Answer 2

Detecting almost any feature in an image is called Object Detection. There is a widely used libray called OpenCV. It has a very simple SDK, although setting up can be a real pain. It is well supported for C/C++ and (nearly well supported for) Python. It took me arnd 3 weeks to train my own Classfier (training), first time I started using OpenCV.

But I would not really depend on this solution entirely and consider my priorities. Also, it is very hard to achieve good rate with custom classifier. Other methods are more time consuming.