Method to use PHP and Qiniu cloud storage interface to realize feature extraction and similarity matching of images

Method of using PHP and Qiniu cloud storage interface to realize image feature extraction and similarity matching

Introduction:
In today's Internet era, the use of image data is becoming more and more widespread. How to effectively Managing and retrieving large amounts of image data becomes an important issue. Image feature extraction and similarity matching are one of the core technologies to achieve efficient image retrieval. This article will introduce how to use PHP and Qiniu cloud storage interface to implement image feature extraction and similarity matching.

1. Introduction to Qiniu Cloud Storage
Qiniu Cloud Storage is a well-known cloud storage service provider in China, providing a wealth of storage and data processing services. In this article, we will use the interface provided by Qiniu Cloud Storage to upload, store and process images.

2. Image feature extraction
Image feature extraction refers to extracting features from the image that can characterize the image content. Commonly used methods include color histograms, edge detection, texture descriptors, etc. This article will take the color histogram as an example to introduce the feature extraction method of images.

1. Install PHP extension
   First, we need to install a PHP extension-OpenCV. OpenCV is an open source computer vision library that can be used for image processing and computer vision tasks. The installation process is as follows:

$ pecl install opencv

2. Use OpenCV to implement color histogram
   We can use OpenCV's Histogram feature detection to implement the color histogram of the image. The code example is as follows:

<?php
  // 加载OpenCV库
  dl('opencv.so');

  // 读取图片
  $img = cvLoadImage('image.jpg');

  // 分割图片为RGB通道
  $channels = array(0, 1, 2);
  $hist_size = array(16, 16, 16);
  $ranges = array(0, 255);

  $hist = cvCreateHist(3, $hist_size, CV_HIST_ARRAY, $ranges);
  cvCalcHist(array($img), $hist);

  // 输出颜色直方图
  for ($z = 0; $z < $hist_size[2]; $z++) {
      for ($y = 0; $y < $hist_size[1]; $y++) {
          for ($x = 0; $x < $hist_size[0]; $x++) {
              $value = cvQueryHistValue_3D($hist, $x, $y, $z);

              echo "($x, $y, $z): $value
";
          }
      }
  }

  // 释放资源
  cvReleaseHist($hist);
  cvReleaseImage($img);
?>

3. Similarity matching
Similarity matching refers to comparing the characteristics of two pictures to determine the degree of similarity between them. In this article, we will introduce a simple similarity matching algorithm-Euclidean distance matching. This algorithm determines how similar two image features are by calculating the Euclidean distance between them.

<?php
  // 计算两个颜色直方图的欧氏距离
  function calculateDistance($hist1, $hist2) {
      $distance = 0;

      for ($z = 0; $z < $hist1->size[2]; $z++) {
          for ($y = 0; $y < $hist1->size[1]; $y++) {
              for ($x = 0; $x < $hist1->size[0]; $x++) {
                  $value1 = cvQueryHistValue_3D($hist1, $x, $y, $z);
                  $value2 = cvQueryHistValue_3D($hist2, $x, $y, $z);

                  $distance += pow($value1 - $value2, 2);
              }
          }
      }

      return sqrt($distance);
  }

  // 读取两个图片的颜色直方图
  $hist1 = cvLoadHist('hist1.yml');
  $hist2 = cvLoadHist('hist2.yml');

  // 计算两个图片的相似度
  $distance = calculateDistance($hist1, $hist2);
  echo "Distance: $distance
";

  // 释放资源
  cvReleaseHist($hist1);
  cvReleaseHist($hist2);
?>

4. Use Qiniu Cloud Storage interface to upload, store and process images
Qiniu Cloud Storage provides a rich set of interfaces, and we can use these interfaces to upload, store and process images.

1. Install Qiniu Cloud Storage SDK
   First, we need to install the PHP SDK of Qiniu Cloud Storage. The installation process is as follows:

$ composer require qiniu/php-sdk

2. Image upload
   Next, we can use the interface provided by Qiniu Cloud Storage SDK to upload images. The code example is as follows:

<?php
  require 'vendor/autoload.php';

  use QiniuAuth;
  use QiniuStorageUploadManager;

  $accessKey = 'your_accessKey';
  $secretKey = 'your_secretKey';
  $bucket = 'your_bucket';
  $key = 'your_key';

  $auth = new Auth($accessKey, $secretKey);
  $token = $auth->uploadToken($bucket);

  $filePath = 'image.jpg';

  $uploadManager = new UploadManager();
  list($ret, $err) = $uploadManager->putFile($token, $key, $filePath);

  echo "Upload result: 
";
  if ($err !== null) {
      var_dump($err);
  } else {
      var_dump($ret);
  }
?>

3. Picture storage
   After the picture is uploaded successfully, we can store the relevant information of the picture in the database for subsequent picture retrieval. The code example is as follows:

<?php
  require 'vendor/autoload.php';

  use QiniuAuth;
  use QiniuStorageUploadManager;
  use QiniuStorageBucketManager;

  $accessKey = 'your_accessKey';
  $secretKey = 'your_secretKey';
  $bucket = 'your_bucket';
  $key = 'your_key';

  $auth = new Auth($accessKey, $secretKey);
  $bucketManager = new BucketManager($auth);

  $fileInfo = $bucketManager->fetch($key, $bucket, $key);
  $persistKey = 'your_persistKey';

  // 存储图片信息到数据库
  // ...

  echo "Save result: 
";
  var_dump($fileInfo);
?>

IV. Summary
This article introduces the method of using PHP and Qiniu cloud storage interface to achieve feature extraction and similarity matching of images. By using the interface provided by Qiniu Cloud Storage, we can easily upload, store and process images. At the same time, the OpenCV library can be used to extract features from images, thereby achieving similarity matching of images.

Through the introduction of this article, we can see that it is a relatively simple and efficient method to use PHP and Qiniu cloud storage interface to achieve feature extraction and similarity matching of images. This method can be applied to image retrieval, album management and other fields to provide users with a better user experience.

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