Convert RGB Image to Grayscale Image by Using OpenCV Importer
This example shows how to convert an RGB image to a grayscale image by using the OpenCV Importer. The converter converts an RGB image to a grayscale image by eliminating the hue and saturation information while retaining the luminance.
In this example, you first import an OpenCV function into Simulink® by using the OpenCV Code Import Wizard. The wizard creates a Simulink library that contains a subsystem and a C Caller block for the specified OpenCV function. The subsystem is then used in a preconfigured Simulink model to accept the RGB image for conversion.
In this example, you learn how to:
Import an OpenCV function into a Simulink library.
Use blocks from a generated library in a Simulink model.
Required Products
Computer Vision Toolbox™ OpenCV Interface for Simulink
Computer Vision Toolbox
Embedded Coder®
Set Up Your C++ Compiler
To build the OpenCV libraries, identify a compatible C++ compiler for your operating
system, as described in Compiler used to build OpenCV libraries. Configure the
identified compiler by using the mex -setup c++ command. For more
information, see Choose a C++ Compiler.
Model Description
This example uses the Simulink model ToGrayScale.slx.
In this model, the subsystem_slwrap_toGrayScale subsystem resides
in the RGBtoGRAY_OpenCVCallerLib library. You create the
subsystem_slwrap_toGrayScale subsystem by using the OpenCV
Importer. The subsystem accepts an RGB image from the Image From
File block and converts it to a grayscale output image. The output is then
displayed on a Video Viewer block.
Step 1: Import OpenCV Function to Create a Simulink Library
To start the OpenCV Importer app, click Apps on the MATLAB® Toolstrip. In the Welcome page, specify the Project name as
RGBtoGRAY. Make sure that the project name does not contain any spaces. Click Next.In Specify OpenCV Library, specify these file locations and click Next.
Project root folder: Specify the path to the example folder as
matlab\toolbox\simulink\supportpackages\simulinkopencv\example\ImageRGBtoGray. This folder contains all the supporting files required to run this example. All your output files are saved to this folder.Source files: Specify the path of the
.cppfile located inside your project folder astoGrayScale.cpp.Include files: Specify the path of the
.hppheader file located inside your project folder astoGrayScale.hpp.
Analyze your library to find the functions and types for import. Once the analysis is completed, click Next. Select the
toGrayScalefunction and click Next.
From What to import, click the I/O Type for img as
InputOutput, and then click Next.
In Create Simulink Library, verify the default values of OpenCV types. By default, Create a single C-caller block for the OpenCV function is selected to create a C Caller block along with the subsystem. To create a Simulink library, click Next.
A Simulink library
RGBtoGRAY_OpenCVCallerLibis created from your OpenCV code. You can use any of the blocks in the library for model simulation. In this example, the subsystemsubsystem_slwrap_toGrayScaleis used.
Step 2: Use Generated Subsystem in Simulink Model
To use the generated subsystem subsystem_slwrap_toGrayScale with
the Simulink model toGrayScale.slx:
In your MATLAB Current Folder, right-click the model
toGrayScale.slxand clickOpenfrom the context menu. Drag the generated subsystem to the model and connect the blocks.Double-click the subsystem and specify these parameter values.
Parameters Values Description Rows 384Number of rows in the output image Columns 512Number of columns in the output image Channels 1Number of channels in the output image Underlying Type uint8Underlying data type of OpenCV Matis Image on Whether input is an image or a matrix Click Apply and then click OK.
Step 3: Simulate the RGB to Gray Convertor
On the Simulink Toolstrip, in the Simulation tab,
click 
to simulate the model. After the simulation is
complete, the Video Viewer block displays the grayscale image of the
input image peppers.png.
