How to perform image thresholding using PHP and OpenCV libraries

Method of image thresholding using PHP and OpenCV libraries

Image processing is one of the important research directions in the field of computer vision, among which image thresholding is a commonly used method. Through image thresholding, we can convert the pixel values ​​in the image into a binary form to facilitate subsequent image segmentation, edge detection and other operations. This article will introduce how to use PHP and OpenCV libraries for image thresholding and give code examples.

First, we need to prepare the installation and configuration of the OpenCV library. To use the OpenCV library in PHP, you can use the PHP extension package php-opencv. We can install the php-opencv extension package through the following steps.

Step 1: Install the OpenCV library

Execute the following command in the terminal to install the OpenCV library:

sudo apt-get update
sudo apt-get install libopencv-dev

Step 2: Install the php-opencv extension package

Execute the following command in the terminal to install the php-opencv extension package:

sudo apt-add-repository ppa:ondrej/php
sudo apt-get update
sudo apt-get install php7.4-opencv

Next, we can use the PHP and OpenCV libraries to threshold the image. The following is a sample code:

<?php

$srcFilePath = 'input.jpg';
$outputFilePath = 'output.jpg';

// 读取图像
$srcImage = cvimread($srcFilePath, cvIMREAD_GRAYSCALE);

// 应用阈值化处理
$binaryImage = new OpenCVBinaryImage();
$binaryImage->adaptiveThreshold($srcImage, 255, cvADAPTIVE_THRESH_MEAN_C, cvTHRESH_BINARY, 11, 2);

// 输出图像
cvimwrite($outputFilePath, $binaryImage);

// 释放资源
unset($srcImage);
unset($binaryImage);

?>

In the above code, the input image is first read through the cvimread function, and the image is converted into a grayscale image using the cvIMREAD_GRAYSCALE parameter .

Next, we create a BinaryImage object and use the adaptiveThreshold function to threshold the grayscale image. The parameters of this function are: input image, maximum threshold, adaptive thresholding method, binarization method, block size, and constant value.

Finally, we use the cvimwrite function to write the thresholded image to the output file.

It should be noted that when using the functions of the OpenCV library, you need to add the cv or OpenCV prefix in front of the function.

Through the above code, we can output the binary image obtained by image thresholding to a file. Of course, we can further perform morphological operations, contour extraction and other processing on the binary image to achieve more image analysis and recognition functions.

To summarize, the method of using PHP and OpenCV libraries for image thresholding is very simple. You only need to install the corresponding libraries and call the corresponding functions. Hope this article helps you!

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