How to use PHP for AI face recognition and identity verification?

With the continuous advancement of science and technology and the rapid development of artificial intelligence technology, AI face recognition and identity verification have become commonly used technical means in modern society. Through AI face recognition and identity verification technology, we can verify the authenticity of users in a very short time and protect the security of system information. PHP is a popular programming language. This article will detail how to use PHP for AI face recognition and identity verification.

1. What is AI face recognition and identity verification technology?

AI face recognition is an artificial intelligence technology that uses computer vision and pattern recognition technology to identify and analyze face images to achieve functions such as population counting, security monitoring, and face retrieval.

Identity verification refers to using a series of technical means, such as face recognition, voice recognition, fingerprint recognition, etc., to determine whether the user's identity information is true and legal.

2. How to use PHP for AI face recognition?

Step 1: Install OpenCV

1. Install PHP

First, you need to install PHP on your computer. You can go to the PHP official website to download and install it.

2. Install OpenCV

OpenCV is an open source computer vision library widely used in the field of computer vision. In order to use PHP for face recognition, you need to install OpenCV version 3.4.

3. Install other library files

In addition to OpenCV, you also need to install some other library files, such as FFmpeg, libWebP, libJPEG-turbo, etc. These library files are all open source, and you can find the download link on the official website for installation.

Step 2: Write code

The following is a simple PHP code snippet that shows how to use OpenCV for face recognition:

// Load the OpenCV library first
if (!function_exists('cvimread')) {
require_once DIR . '/cv.php';
}

//Get the image and detect the face
$image = cvimread('test.jpg');
$face_cascade = cvCascadeClassifier::cv('haarcascade_frontalface_alt.xml');
$faces = $face_cascade ->detectMultiScale($image, 1.3, 5);

// Draw detection results
foreach ($faces as $face) {
cvectangle($image, $face, [255,255,255] , 3);
}

// Output result
header('Content-Type: image/jpeg');
cvimwrite('test_output.jpg', $image);
echo file_get_contents('test_output.jpg');

?>

In this code snippet, we load the image file test.jpg through the imread() function, and then use CascadeClassifier class and haarcascade_frontalface_alt.xml file for face detection. Finally, the detection box is drawn using the rectangle() function and the resulting image is saved using the imwrite() function.

3. How to use PHP for authentication?

Authentication relies on face recognition technology, so we can use the PHP code introduced in the previous section for face recognition. When we successfully identify the user's face, we can compare the recognition result with the user's pre-stored information to perform identity verification.

The following is a simple PHP code snippet that shows how to use face recognition for authentication:

// Load the OpenCV library first
if (!function_exists('cvimread')) {
require_once DIR . '/cv.php';
}

// Get the image used for matching
$known_image = cvimread('known_face.jpg');

// Get the image that needs to be matched
$user_image = cvimread('user_face.jpg');

/ / Match two images
$face_recognizer = cv aceLBPHFaceRecognizer::create();
$face_recognizer->train([$known_image], [1]);
[$label, $confidence] = $face_recognizer->predict($user_image);

// Compare the results and perform identity verification
if ($label === 1 && $confidence < 70) {
echo " Authentication successful!";
} else {
echo "Authentication failed!";
}

?>

In this code snippet, we first Use the imread() function to load the image used for matching and the image that needs to be matched. Then, use the LBPHFaceRecognizer class and train() function for training, and finally predict() function for prediction.

When we get the prediction results, we can compare the results with the pre-stored information to perform identity verification.

Conclusion:

Through this article, we have introduced in detail how to use PHP for AI face recognition and authentication. Although specific optimization and implementation are required for different scenarios when using this technology, the basic process and code snippets introduced in this article can allow readers to understand the basic principles of AI face recognition and identity verification, and Help readers learn and use this technology in depth.

The above is the detailed content of How to use PHP for AI face recognition and identity verification?. For more information, please follow other related articles on the PHP Chinese website!