如何在不考虑缩放、旋转的情况下使用php比较图像相似性？_Php_Image Processing_Similarity

如何在不考虑缩放、旋转的情况下使用php比较图像相似性？

php image-processing

如何在不考虑缩放、旋转的情况下使用php比较图像相似性？,php,image-processing,similarity,Php,Image Processing,Similarity,我想比较以下图片之间的相似性。根据我的要求，我想确定所有这些图像都是相似的，因为它们使用了相同的颜色，相同的剪贴画。这些图像的唯一区别是旋转、缩放和剪贴画的放置。因为所有3件t恤都使用了相同的颜色和剪贴画，所以我想将所有3张图片识别为相似的。我尝试了中描述的方法。但它并没有根据我的要求给出正确的结果。如何识别这些相似的图像？你有什么建议吗？请帮帮我下面的图像应被识别为与上面的图像不同。（即使T恤颜色相同，剪贴画也不同。最后一件T恤与上面不同，因为它使用了相同的剪贴画，但使用了两次。）移

我想比较以下图片之间的相似性。根据我的要求，我想确定所有这些图像都是相似的，因为它们使用了相同的颜色，相同的剪贴画。这些图像的唯一区别是旋转、缩放和剪贴画的放置。因为所有3件t恤都使用了相同的颜色和剪贴画，所以我想将所有3张图片识别为相似的。我尝试了中描述的方法。但它并没有根据我的要求给出正确的结果。如何识别这些相似的图像？你有什么建议吗？请帮帮我

下面的图像应被识别为与上面的图像不同。（即使T恤颜色相同，剪贴画也不同。最后一件T恤与上面不同，因为它使用了相同的剪贴画，但使用了两次。）

移动到GitHub 因为这个问题很有趣，所以我将整个问题转移到GitHub，在那里您可以找到当前的实现：

原始答案我做了一个非常简单的方法，使用img resize并比较调整大小的图像的平均颜色

$binEqual = [
    file_get_contents('http://i.stack.imgur.com/D8ct1.png'),
    file_get_contents('http://i.stack.imgur.com/xNZt1.png'),
    file_get_contents('http://i.stack.imgur.com/kjGjm.png')
];

$binDiff = [
    file_get_contents('http://i.stack.imgur.com/WIOHs.png'),
    file_get_contents('http://i.stack.imgur.com/ljoBT.png'),
    file_get_contents('http://i.stack.imgur.com/qEKSK.png')
];


function getAvgColor($bin, $size = 10) {

    $target = imagecreatetruecolor($size, $size);
    $source = imagecreatefromstring($bin);

    imagecopyresized($target, $source, 0, 0, 0, 0, $size, $size, imagesx($source), imagesy($source));

    $r = $g = $b = 0;

    foreach(range(0, $size - 1) as $x) {
        foreach(range(0, $size - 1) as $y) {
            $rgb = imagecolorat($target, $x, $y);
            $r += $rgb >> 16;
            $g += $rgb >> 8 & 255;
            $b += $rgb & 255;
        }
    }   

    unset($source, $target);

    return (floor($r / $size ** 2) << 16) +  (floor($g / $size ** 2) << 8)  + floor($b / $size ** 2);
}

function compAvgColor($c1, $c2, $tolerance = 4) {

    return abs(($c1 >> 16) - ($c2 >> 16)) <= $tolerance && 
           abs(($c1 >> 8 & 255) - ($c2 >> 8 & 255)) <= $tolerance &&
           abs(($c1 & 255) - ($c2 & 255)) <= $tolerance;
}

$perms = [[0,1],[0,2],[1,2]];

foreach($perms as $perm) {
    var_dump(compAvgColor(getAvgColor($binEqual[$perm[0]]), getAvgColor($binEqual[$perm[1]])));
}

foreach($perms as $perm) {
    var_dump(compAvgColor(getAvgColor($binDiff[$perm[0]]), getAvgColor($binDiff[$perm[1]])));
}

更高级的实现要比较的空T恤：

在此计算中，背景被忽略，这会导致平均颜色的较大差异

最终实现（OOP）很有趣的话题。所以我试着把它调高一点。这现在是一个完整的OOP实现。现在，您可以创建一个新图像，并减去它的一些遮罩，以消除背景。然后可以使用比较方法将一个图像与另一个图像进行比较。为了限制计算，最好先调整图像大小（遮罩始终适合当前图像）

比较算法将两幅图像自分块成若干块，然后消除几乎等于白色平均颜色的块，然后比较所有剩余块排列的平均颜色

Class Image {

    const HASH_SIZE = 8;
    const AVG_SIZE = 10;

    private $img = null;

    public function __construct($resource)
    {
        $this->img = $resource;;
    }

    private function permute(array $a1, array $a2) {
        $perms = array();
        for($i = 0; $i < sizeof($a1); $i++) {
            for($j = $i; $j < sizeof($a2); $j++) {
                if ($i != $j) {
                    $perms[] = [$a1[$i], 
                    $a2[$j]];
                }
            }
        }

        return $perms;
    }

    public function compare(Image $comp) {
        $avgComp = array();

        foreach($comp->chunk(25) as $chunk) {
            $avgComp[] = $chunk->avg();
        }

        $avgOrg = array();

        foreach($this->chunk(25) as $chunk) {
            $avgOrg[] = $chunk->avg();
        }

        $white = Color::fromInt(0xFFFFFF);

        $avgComp = array_values(array_filter($avgComp, function(Color $color) use ($white){
            return $white->compare($color, 1000);
        }));

        $avgOrg = array_values(array_filter($avgOrg, function(Color $color) use ($white){
            return $white->compare($color, 1000);
        }));

        $equal = 0;
        $pairs = $this->permute($avgOrg, $avgComp);

        foreach($pairs as $pair) {
            $equal += $pair[0]->compare($pair[1], 100) ? 1 : 0;
        }

        return ($equal / sizeof($pairs));
    }

    public function substract(Image $mask, $tolerance = 50)
    {
        $size = $this->size();

        if ($mask->size() != $size) {
            $mask = $mask->resize($size);
        }

        for ($x = 0; $x < $size[0]; $x++) {
            for ($y = 0; $y < $size[1]; $y++) {
                if ($this->colorat($x, $y)->compare($mask->colorat($x, $y), $tolerance))
                    imagesetpixel($this->img, $x, $y, 0xFFFFFF);
            }
        }

        return $this;
    }

    public function avg($size = 10)
    {
        $target = $this->resize([self::AVG_SIZE, self::AVG_SIZE]);

        $avg   = Color::fromInt(0x000000);
        $white = Color::fromInt(0xFFFFFF);  

        for ($x = 0; $x < self::AVG_SIZE; $x++) {
            for ($y = 0; $y < self::AVG_SIZE; $y++) {
                $color = $target->colorat($x, $y);
                if (!$color->compare($white, 10))
                    $avg->mix($color);
            }
        }

        return $avg;
    }

    public function colorat($x, $y)
    {
        return Color::fromInt(imagecolorat($this->img, $x, $y));
    }

    public function chunk($chunkSize = 10)
    {
        $collection = new ImageCollection();
        $size = $this->size();

        for($x = 0; $x < $size[0]; $x += $chunkSize) {
            for($y = 0; $y < $size[1]; $y += $chunkSize) {
                switch (true) {
                    case ($x + $chunkSize > $size[0] && $y + $chunkSize > $size[1]):
                        $collection->push($this->slice(['x' => $x, 'y' => $y, 'height' => $size[0] - $x, 'width' => $size[1] - $y]));
                        break;
                    case ($x + $chunkSize > $size[0]):
                        $collection->push($this->slice(['x' => $x, 'y' => $y, 'height' => $size[0] - $x, 'width' => $chunkSize]));
                        break;
                    case ($y + $chunkSize > $size[1]):
                        $collection->push($this->slice(['x' => $x, 'y' => $y, 'height' => $chunkSize, 'width' => $size[1] - $y]));
                        break;
                    default:
                        $collection->push($this->slice(['x' => $x, 'y' => $y, 'height' => $chunkSize, 'width' => $chunkSize]));
                        break;
                }
            }
        }

        return $collection;
    }

    public function slice(array $rect)
    {
        return Image::fromResource(imagecrop($this->img, $rect));
    }

    public function size()
    {
        return [imagesx($this->img), imagesy($this->img)];
    }

    public function resize(array $size = array(100, 100))
    {
        $target = imagecreatetruecolor($size[0], $size[1]);
        imagecopyresized($target, $this->img, 0, 0, 0, 0, $size[0], $size[1], imagesx($this->img), imagesy($this->img));

        return Image::fromResource($target);
    }

    public function show()
    {
        header("Content-type: image/png");
        imagepng($this->img);
        die();
    }

    public function save($name = null, $path = '') {
        if ($name === null) {
            $name = $this->hash();
        }

        imagepng($this->img, $path . $name . '.png');

        return $this;
    }

    public function hash()
    {
                // Resize the image.
        $resized = imagecreatetruecolor(self::HASH_SIZE, self::HASH_SIZE);
        imagecopyresampled($resized, $this->img, 0, 0, 0, 0, self::HASH_SIZE, self::HASH_SIZE, imagesx($this->img), imagesy($this->img));
        // Create an array of greyscale pixel values.
        $pixels = [];
        for ($y = 0; $y < self::HASH_SIZE; $y++)
        {
            for ($x = 0; $x < self::HASH_SIZE; $x++)
            {
                $rgb = imagecolorsforindex($resized, imagecolorat($resized, $x, $y));
                $pixels[] = floor(($rgb['red'] + $rgb['green'] + $rgb['blue']) / 3);
            }
        }
        // Free up memory.
        imagedestroy($resized);
        // Get the average pixel value.
        $average = floor(array_sum($pixels) / count($pixels));
        // Each hash bit is set based on whether the current pixels value is above or below the average.
        $hash = 0; $one = 1;
        foreach ($pixels as $pixel)
        {
            if ($pixel > $average) $hash |= $one;
            $one = $one << 1;
        }
        return $hash;
    }

    public static function fromResource($resource)
    {
        return new self($resource);
    }

    public static function fromBin($binf)
    {
        return new self(imagecreatefromstring($bin));
    }

    public static function fromFile($path)
    {
        return new self(imagecreatefromstring(file_get_contents($path)));
    }
}

class ImageCollection implements IteratorAggregate
{
    private $images = array();

    public function __construct(array $images = array())
    {
        $this->images = $images;
    }

    public function push(Image $image) {
        $this->images[] = $image;
        return $this;
    }

    public function pop()
    {
        return array_pop($this->images);
    }

    public function save()
    {
        foreach($this->images as $image)
        {
            $image->save();
        }

        return $this;
    }

    public function getIterator() {
        return new ArrayIterator($this->images);
    }
}

class Color {
    private $r = 0;
    private $g = 0;
    private $b = 0;

    public function __construct($r = 0, $g = 0, $b = 0)
    {
        $this->r = $r;
        $this->g = $g;
        $this->b = $b;
    }

    public function r()
    {
        return $this->r;
    }

    public function g()
    {
        return $this->g;
    }

    public function b()
    {
        return $this->b;
    }

    public function toInt()
    {
        return $this->r << 16 + $this->g << 8 + $this->b;
    }

    public function toRgb()
    {
        return [$this->r, $this->g, $this->b];  
    }

    public function mix(Color $color)
    {
        $this->r = round($this->r + $color->r() / 2);
        $this->g = round($this->g + $color->g() / 2);
        $this->b = round($this->b + $color->b() / 2);
    }

    public function compare(Color $color, $tolerance = 500)
    {
        list($r1, $g1, $b1) = $this->toRgb();
        list($r2, $g2, $b2) = $color->toRgb();

        $diff = round(sqrt(pow($r1 - $r2, 2) + pow($g1 - $g2, 2) + pow($b1 - $b2, 2)));

        //printf("Comp r(%s : %s), g(%s : %s), b(%s : %s) Diff %s \n", $r1, $r2, $g1, $g2, $b1, $b2, $diff);

        return  $diff <= $tolerance;
    }

    public static function fromInt($int) {
        return new self($int >> 16, $int >> 8 & 255, $int & 255);
    }
}

$mask = Image::fromFile('http://i.stack.imgur.com/gfn5A.png');

$image1 = Image::fromFile('http://i.stack.imgur.com/D8ct1.png')->resize([50, 100])->substract($mask, 100);
$image2 = Image::fromFile('http://i.stack.imgur.com/xNZt1.png')->resize([50, 100])->substract($mask, 100);
$image3 = Image::fromFile('http://i.stack.imgur.com/kjGjm.png')->resize([50, 100])->substract($mask, 100);

$other1 = Image::fromFile('http://i.stack.imgur.com/WIOHs.png')->resize([50, 100])->substract($mask, 100);
$other2 = Image::fromFile('http://i.stack.imgur.com/ljoBT.png')->resize([50, 100])->substract($mask, 100);
$other3 = Image::fromFile('http://i.stack.imgur.com/qEKSK.png')->resize([50, 100])->substract($mask, 100);


echo "Equal\n";
var_dump(
    $image1->compare($image2),
    $image1->compare($image3),
    $image2->compare($image3)
);

echo "Image 1 to Other\n";
var_dump(
    $image1->compare($other1),
    $image1->compare($other2),
    $image1->compare($other3)
);

echo "Image 2 to Other\n";
var_dump(
    $image2->compare($other1),
    $image2->compare($other2),
    $image2->compare($other3)
);

echo "Image 3 to Other\n";
var_dump(
    $image3->compare($other1),
    $image3->compare($other2),
    $image3->compare($other3)
);

我并不是说我真的知道关于这个话题的任何事情，我认为这个话题通常被称为“愿景”

然而，我要做的是以下几点：

流量：

Posterise，将颜色/阴影的数量降至最低（猜测）
去除两种最大的颜色（白色+衬衫）

比较剩余调色板，如果方案差异太大，则失败

计算剩余“色块”周围的粗糙多边形（请参见）

比较每个图像中的多边形数和最大多边形的角度数和角度值（不是大小），然后失败或通过

这种设置的主要问题是舍入。。。在对一种颜色进行后处理时，这正是两种颜色之间的中间点。。。有时是A色，有时是B色。
我猜多边形也是一样。
相似计算两个等维图像之间的标准化互相关相似性度量。归一化互相关度量度量两个图像的相似程度，而不是它们的不同程度。ncc度量值的范围介于0（不相似）和1（相似）之间。如果mode=g，则两幅图像将转换为灰度。如果mode=rgb，则首先将两个图像转换为colorspace=rgb。接下来，将为每个信道计算ncc相似性度量。最后，它们将组合成rms值。注意：此度量不适用于恒定颜色通道，因为它为该通道生成ncc度量=0/0。因此，不建议对启用了完全不透明或完全透明alpha通道的图像运行脚本
试试这个api

http://www.phpclasses.org/package/8255-PHP-Compare-two-images-to-find-if-they-are-similar.html

正如有人提到的，除了计算图像的直方图并对其进行比较之外，其他任何事情都不容易实现。下面是一个示例，它给出了有关图像的正确结果。这里的关键点是如何在峰值颜色级别的数量和它们的可接受数量之间取得正确的平衡（
相似性（$histograms，$levels=30，$ough=28）
）

函数直方图（$images）{ foreach（$img形式的图像）{ $image=imagecreatefrompng（$img）； $width=imagesx（$image）； $height=imagesy（$image）； $num_像素=$width*$height； $histogram=[]；对于（$x=0；$x<$width；$x++）{ 对于（$y=0；$y<$height；$y++）{ $rgb=imagecolorat（$image，$y，$x）； $rgb=[$rgb>>16，（$rgb>>8）和0xFF，$rgb和0xFF]； $histo_v=（int）round（$rgb[0]+$rgb[1]+$rgb[02]）/3）； $histogram[$histo_v]=数组密钥存在（$histo_v，$histogram）？$histogram[$histo_v]+$histo_v/$num_像素：$histo_v/$num_像素； } } $histograms[$img]=$histogram； arsort（$histograms[$img]）； } 返回$直方图； } 函数相似性（$histograms，$levels=30，$ough=28）{ $keys=数组_键（$直方图）； $output=[]；对于（$x=0；$x<计数（$直方图）-1；$x++）{ 对于（$y=$x+1；$y<计数（$直方图）；$y++）{ $similarity=count（数组相交键（数组切片（$histograms[$keys[$x]]，0，$levels，true），数组切片（$histograms[$keys[$y]]，0，$levels，true））；如果（$similarity>$ough）$output[]=[$keys[$x]，$keys[$y]，$similarity]； } } 返回$output； } $histograms=直方图（['http://i.stack.imgur.com/D8ct1.png', 'http://i.stack.imgur.com/xNZt1.png', 'http://i.stack.imgur.com/kjGjm.png', 'http://i.stack.imgur.com/WIOHs.png', 'http://i.stack.imgur.com/ljoBT.png', 'http://i.stack.imgur.com/qEKSK.png' ] ); $相似性=相似性（$直方图）；打印（相似性）； /* 排列 ( [0]=>阵列 ( [0] => http://i.stack.imgur.com/D8ct1.png Equal Comp r(101 : 101), g(46 : 46), b(106 : 106) Diff 0 bool(true) Comp r(121 : 101), g(173 : 46), b(249 : 106) Diff 192 bool(true) Comp r(219 : 101), g(179 : 46), b(268 : 106) Diff 241 bool(true) Comp r(121 : 101), g(173 : 46), b(249 : 106) Diff 192 bool(true) Comp r(121 : 121), g(173 : 173), b(249 : 249) Diff 0 bool(true) Comp r(121 : 219), g(173 : 179), b(249 : 268) Diff 100 bool(true) Comp r(219 : 101), g(179 : 46), b(268 : 106) Diff 241 bool(true) Comp r(219 : 121), g(179 : 173), b(268 : 249) Diff 100 bool(true) Comp r(219 : 219), g(179 : 179), b(268 : 268) Diff 0 bool(true) Different Comp r(101 : 446), g(46 : 865), b(106 : 1242) Diff 1442 bool(false) Comp r(121 : 446), g(173 : 865), b(249 : 1242) Diff 1253 bool(false) Comp r(219 : 446), g(179 : 865), b(268 : 1242) Diff 1213 bool(false) Comp r(121 : 446), g(173 : 865), b(249 : 1242) Diff 1253 bool(false) Comp r(121 : 654), g(173 : 768), b(249 : 1180) Diff 1227 bool(false) Comp r(121 : 708), g(173 : 748), b(249 : 1059) Diff 1154 bool(false) Comp r(219 : 446), g(179 : 865), b(268 : 1242) Diff 1213 bool(false) Comp r(219 : 654), g(179 : 768), b(268 : 1180) Diff 1170 bool(false) Comp r(219 : 708), g(179 : 748), b(268 : 1059) Diff 1090 bool(false) Class Image { const HASH_SIZE = 8; const AVG_SIZE = 10; private $img = null; public function __construct($resource) { $this->img = $resource;; } private function permute(array $a1, array $a2) { $perms = array(); for($i = 0; $i < sizeof($a1); $i++) { for($j = $i; $j < sizeof($a2); $j++) { if ($i != $j) { $perms[] = [$a1[$i], $a2[$j]]; } } } return $perms; } public function compare(Image $comp) { $avgComp = array(); foreach($comp->chunk(25) as $chunk) { $avgComp[] = $chunk->avg(); } $avgOrg = array(); foreach($this->chunk(25) as $chunk) { $avgOrg[] = $chunk->avg(); } $white = Color::fromInt(0xFFFFFF); $avgComp = array_values(array_filter($avgComp, function(Color $color) use ($white){ return $white->compare($color, 1000); })); $avgOrg = array_values(array_filter($avgOrg, function(Color $color) use ($white){ return $white->compare($color, 1000); })); $equal = 0; $pairs = $this->permute($avgOrg, $avgComp); foreach($pairs as $pair) { $equal += $pair[0]->compare($pair[1], 100) ? 1 : 0; } return ($equal / sizeof($pairs)); } public function substract(Image $mask, $tolerance = 50) { $size = $this->size(); if ($mask->size() != $size) { $mask = $mask->resize($size); } for ($x = 0; $x < $size[0]; $x++) { for ($y = 0; $y < $size[1]; $y++) { if ($this->colorat($x, $y)->compare($mask->colorat($x, $y), $tolerance)) imagesetpixel($this->img, $x, $y, 0xFFFFFF); } } return $this; } public function avg($size = 10) { $target = $this->resize([self::AVG_SIZE, self::AVG_SIZE]); $avg = Color::fromInt(0x000000); $white = Color::fromInt(0xFFFFFF); for ($x = 0; $x < self::AVG_SIZE; $x++) { for ($y = 0; $y < self::AVG_SIZE; $y++) { $color = $target->colorat($x, $y); if (!$color->compare($white, 10)) $avg->mix($color); } } return $avg; } public function colorat($x, $y) { return Color::fromInt(imagecolorat($this->img, $x, $y)); } public function chunk($chunkSize = 10) { $collection = new ImageCollection(); $size = $this->size(); for($x = 0; $x < $size[0]; $x += $chunkSize) { for($y = 0; $y < $size[1]; $y += $chunkSize) { switch (true) { case ($x + $chunkSize > $size[0] && $y + $chunkSize > $size[1]): $collection->push($this->slice(['x' => $x, 'y' => $y, 'height' => $size[0] - $x, 'width' => $size[1] - $y])); break; case ($x + $chunkSize > $size[0]): $collection->push($this->slice(['x' => $x, 'y' => $y, 'height' => $size[0] - $x, 'width' => $chunkSize])); break; case ($y + $chunkSize > $size[1]): $collection->push($this->slice(['x' => $x, 'y' => $y, 'height' => $chunkSize, 'width' => $size[1] - $y])); break; default: $collection->push($this->slice(['x' => $x, 'y' => $y, 'height' => $chunkSize, 'width' => $chunkSize])); break; } } } return $collection; } public function slice(array $rect) { return Image::fromResource(imagecrop($this->img, $rect)); } public function size() { return [imagesx($this->img), imagesy($this->img)]; } public function resize(array $size = array(100, 100)) { $target = imagecreatetruecolor($size[0], $size[1]); imagecopyresized($target, $this->img, 0, 0, 0, 0, $size[0], $size[1], imagesx($this->img), imagesy($this->img)); return Image::fromResource($target); } public function show() { header("Content-type: image/png"); imagepng($this->img); die(); } public function save($name = null, $path = '') { if ($name === null) { $name = $this->hash(); } imagepng($this->img, $path . $name . '.png'); return $this; } public function hash() { // Resize the image. $resized = imagecreatetruecolor(self::HASH_SIZE, self::HASH_SIZE); imagecopyresampled($resized, $this->img, 0, 0, 0, 0, self::HASH_SIZE, self::HASH_SIZE, imagesx($this->img), imagesy($this->img)); // Create an array of greyscale pixel values. $pixels = []; for ($y = 0; $y < self::HASH_SIZE; $y++) { for ($x = 0; $x < self::HASH_SIZE; $x++) { $rgb = imagecolorsforindex($resized, imagecolorat($resized, $x, $y)); $pixels[] = floor(($rgb['red'] + $rgb['green'] + $rgb['blue']) / 3); } } // Free up memory. imagedestroy($resized); // Get the average pixel value. $average = floor(array_sum($pixels) / count($pixels)); // Each hash bit is set based on whether the current pixels value is above or below the average. $hash = 0; $one = 1; foreach ($pixels as $pixel) { if ($pixel > $average) $hash |= $one; $one = $one << 1; } return $hash; } public static function fromResource($resource) { return new self($resource); } public static function fromBin($binf) { return new self(imagecreatefromstring($bin)); } public static function fromFile($path) { return new self(imagecreatefromstring(file_get_contents($path))); } } class ImageCollection implements IteratorAggregate { private $images = array(); public function __construct(array $images = array()) { $this->images = $images; } public function push(Image $image) { $this->images[] = $image; return $this; } public function pop() { return array_pop($this->images); } public function save() { foreach($this->images as $image) { $image->save(); } return $this; } public function getIterator() { return new ArrayIterator($this->images); } } class Color { private $r = 0; private $g = 0; private $b = 0; public function __construct($r = 0, $g = 0, $b = 0) { $this->r = $r; $this->g = $g; $this->b = $b; } public function r() { return $this->r; } public function g() { return $this->g; } public function b() { return $this->b; } public function toInt() { return $this->r << 16 + $this->g << 8 + $this->b; } public function toRgb() { return [$this->r, $this->g, $this->b]; } public function mix(Color $color) { $this->r = round($this->r + $color->r() / 2); $this->g = round($this->g + $color->g() / 2); $this->b = round($this->b + $color->b() / 2); } public function compare(Color $color, $tolerance = 500) { list($r1, $g1, $b1) = $this->toRgb(); list($r2, $g2, $b2) = $color->toRgb(); $diff = round(sqrt(pow($r1 - $r2, 2) + pow($g1 - $g2, 2) + pow($b1 - $b2, 2))); //printf("Comp r(%s : %s), g(%s : %s), b(%s : %s) Diff %s \n", $r1, $r2, $g1, $g2, $b1, $b2, $diff); return $diff <= $tolerance; } public static function fromInt($int) { return new self($int >> 16, $int >> 8 & 255, $int & 255); } } $mask = Image::fromFile('http://i.stack.imgur.com/gfn5A.png'); $image1 = Image::fromFile('http://i.stack.imgur.com/D8ct1.png')->resize([50, 100])->substract($mask, 100); $image2 = Image::fromFile('http://i.stack.imgur.com/xNZt1.png')->resize([50, 100])->substract($mask, 100); $image3 = Image::fromFile('http://i.stack.imgur.com/kjGjm.png')->resize([50, 100])->substract($mask, 100); $other1 = Image::fromFile('http://i.stack.imgur.com/WIOHs.png')->resize([50, 100])->substract($mask, 100); $other2 = Image::fromFile('http://i.stack.imgur.com/ljoBT.png')->resize([50, 100])->substract($mask, 100); $other3 = Image::fromFile('http://i.stack.imgur.com/qEKSK.png')->resize([50, 100])->substract($mask, 100); echo "Equal\n"; var_dump( $image1->compare($image2), $image1->compare($image3), $image2->compare($image3) ); echo "Image 1 to Other\n"; var_dump( $image1->compare($other1), $image1->compare($other2), $image1->compare($other3) ); echo "Image 2 to Other\n"; var_dump( $image2->compare($other1), $image2->compare($other2), $image2->compare($other3) ); echo "Image 3 to Other\n"; var_dump( $image3->compare($other1), $image3->compare($other2), $image3->compare($other3) ); Equal float(0.47619047619048) float(0.53333333333333) float(0.4) Image 1 to Other int(0) int(0) int(0) Image 2 to Other int(0) int(0) int(0) Image 3 to Other int(0) int(0) int(0) http://www.phpclasses.org/package/8255-PHP-Compare-two-images-to-find-if-they-are-similar.html function histograms( $images ) { foreach( $images as $img ) { $image = imagecreatefrompng( $img ); $width = imagesx( $image ); $height = imagesy( $image ); $num_pixels = $width * $height; $histogram = []; for ( $x = 0; $x < $width; $x++ ) { for ( $y = 0; $y < $height; $y++ ) { $rgb = imagecolorat( $image, $y, $x ); $rgb = [ $rgb >> 16, ( $rgb >> 8 ) & 0xFF, $rgb & 0xFF ]; $histo_v = (int) round( ( $rgb[0] + $rgb[1] + $rgb[02] ) / 3 ); $histogram[ $histo_v ] = array_key_exists( $histo_v, $histogram ) ? $histogram[ $histo_v ] + $histo_v/$num_pixels : $histo_v/$num_pixels; } } $histograms[$img] = $histogram; arsort( $histograms[$img] ); } return $histograms; } function similarity( $histograms, $levels = 30, $enough = 28 ) { $keys = array_keys( $histograms ); $output = []; for ( $x = 0; $x < count( $histograms ) - 1; $x++ ) { for ( $y = $x + 1; $y < count( $histograms ); $y++ ) { $similarity = count( array_intersect_key( array_slice( $histograms[ $keys[$x] ], 0, $levels, true ), array_slice( $histograms[ $keys[$y] ], 0, $levels, true ) ) ); if ( $similarity > $enough ) $output[] = [ $keys[$x], $keys[$y], $similarity ]; } } return $output; } $histograms = histograms( [ 'http://i.stack.imgur.com/D8ct1.png', 'http://i.stack.imgur.com/xNZt1.png', 'http://i.stack.imgur.com/kjGjm.png', 'http://i.stack.imgur.com/WIOHs.png', 'http://i.stack.imgur.com/ljoBT.png', 'http://i.stack.imgur.com/qEKSK.png' ] ); $similarity = similarity( $histograms ); print_r( $similarity ); /* Array ( [0] => Array ( [0] => http://i.stack.imgur.com/D8ct1.png [1] => http://i.stack.imgur.com/xNZt1.png [2] => 30 ) [1] => Array ( [0] => http://i.stack.imgur.com/D8ct1.png [1] => http://i.stack.imgur.com/kjGjm.png [2] => 30 ) [2] => Array ( [0] => http://i.stack.imgur.com/D8ct1.png [1] => http://i.stack.imgur.com/qEKSK.png [2] => 29 ) [3] => Array ( [0] => http://i.stack.imgur.com/xNZt1.png [1] => http://i.stack.imgur.com/kjGjm.png [2] => 30 ) [4] => Array ( [0] => http://i.stack.imgur.com/xNZt1.png [1] => http://i.stack.imgur.com/qEKSK.png [2] => 29 ) [5] => Array ( [0] => http://i.stack.imgur.com/kjGjm.png [1] => http://i.stack.imgur.com/qEKSK.png [2] => 29 ) ) */