gusucode.com > visionhdl工具箱matlab源码程序 > visionhdl/visionhdlexamples/EnhancedEdgeDetectionHDLExample.m
%% Enhanced Edge Detection from Noisy Color Video
% This example demonstrates how to develop a complex pixel-stream video
% processing algorithm, accelerate its simulation using MATLAB Coder(TM),
% and generate HDL code from the design. The algorithm enhances the edge
% detection from noisy color video.You must have a MATLAB Coder license to
% run this example.
%
% It is beneficial to go over both
% <matlab:showdemo('PixelStreamingDesignHDLExample') Pixel-Streaming Design in MATLAB>
% and
% <matlab:showdemo('DesignAccelerationHDLExample') Accelerate a Pixel-Streaming Design Using MATLAB Coder>
% examples before proceeding to this one.
%% Test Bench
% In the
% <matlab:edit(fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples','EnhancedEdgeDetectionHDLTestBench.m'))
% EnhancedEdgeDetectionHDLTestBench> file,
% the *videoIn* object reads each frame from a color video source, and the
% |imnoise| function adds salt and pepper noise. This noisy color image is
% passed to the *frm2pix* object, which converts the full image frame to a
% stream of pixels and control structures. The function
% <matlab:edit(fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples','EnhancedEdgeDetectionHDLDesign.m')) EnhancedEdgeDetectionHDLDesign>
% is then called to process one pixel (and its associated control
% structure) at a time. After we process the entire pixel-stream and
% collect the output stream, the *pix2frm* object converts the output
% stream to full-frame video. A full-frame reference design
% <matlab:edit(fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples','EnhancedEdgeDetectionHDLReference.m')) EnhancedEdgeDetectionHDLReference>
% is also called to process the noisy color image. Its output is compared
% with that of the pixel-stream design.
% The function <matlab:edit(fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples','EnhancedEdgeDetectionHDLViewer.m')) EnhancedEdgeDetectionHDLViewer>
% is called to display video outputs.
%
% The workflow above is implemented in the following lines of
% <matlab:edit(fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples','EnhancedEdgeDetectionHDLTestBench.m')) EnhancedEdgeDetectionHDLTestBench>.
%
% ...
% frmIn = zeros(actLine,actPixPerLine,3,'uint8');
% for f = 1:numFrm
% frmFull = step(videoIn); % Get a new frame
% frmIn = imnoise(frmFull,'salt & pepper'); % Add noise
%
% % Call the pixel-stream design
% [pixInVec,ctrlInVec] = step(frm2pix,frmIn);
% for p = 1:numPixPerFrm
% [pixOutVec(p),ctrlOutVec(p)] = EnhancedEdgeDetectionHDLDesign(pixInVec(p,:),ctrlInVec(p));
% end
% frmOut = step(pix2frm,pixOutVec,ctrlOutVec);
%
% % Call the full-frame reference design
% [frmGray,frmDenoise,frmEdge,frmRef] = visionhdlenhancededge_reference(frmIn);
%
% % Compare the results
% if nnz(imabsdiff(frmRef,frmOut))>20
% fprintf('frame %d: reference and design output differ in more than 20 pixels.\n',f);
% return;
% end
%
% % Display the results
% EnhancedEdgeDetectionHDLViewer(actPixPerLine,actLine,[frmGray frmDenoise uint8(255*[frmEdge frmOut])],[frmFull frmIn]);
% end
% ...
%
% Since frmGray and frmDenoise are uint8 data type while frmEdge and frmOut
% are logical, *uint8(255x[frmEdge frmOut])* maps logical false and true
% to uint8(0) and uint8(255), respectively, so that matrices can be
% concatenated.
%
% Both *frm2pix* and *pix2frm* are used to convert between full-frame and
% pixel-stream domains. The inner for-loop performs pixel-stream
% processing. The rest of the test bench performs full-frame processing.
%
% Before the test bench terminates, frame rate is displayed to illustrate
% the simulation speed.
%
% For the functions that do not support C code generation, such as |tic|,
% |toc|, |imnoise|, and |fprintf| in this example, use *coder.extrinsic* to
% declare them as extrinsic functions. Extrinsic functions are excluded
% from MEX generation. The simulation executes them in the regular
% interpreted mode. Since |imnoise| is not included in the C code generation
% process, the compiler cannot infer the data type and size of frmIn.
% To fill in this missing piece, we add the statement
% *frmIn = zeros(actLine,actPixPerLine,3,'uint8')* before the outer for-loop.
%% Pixel-Stream Design
% The function
% <matlab:edit(fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples','EnhancedEdgeDetectionHDLDesign.m')) EnhancedEdgeDetectionHDLDesign>
% accepts a pixel stream and a structure consisting of five control signals, and returns a modified
% pixel stream and control structure. For more information on the streaming
% pixel protocol used by System objects from the Vision HDL Toolbox, see
% the
% <matlab:helpview(fullfile(docroot,'visionhdl','ug','streaming-pixel-interface.html')) documentation>.
%
% In this example, the *rgb2gray* object converts a color image to grayscale,
% *medfil* removes the salt and pepper noise.
% *sobel* highlights the edge. Finally,
% the *mclose* object performs morphological closing to enhance the edge
% output. The code is shown below.
%
% [pixGray,ctrlGray] = step(rgb2gray,pixIn,ctrlIn); % Convert RGB to grayscale
% [pixDenoise,ctrlDenoise] = step(medfil,pixGray,ctrlGray); % Remove noise
% [pixEdge,ctrlEdge] = step(sobel,pixDenoise,ctrlDenoise); % Detect edges
% [pixClose,ctrlClose] = step(mclose,pixEdge,ctrlEdge); % Apply closing
%% Full-Frame Reference Design
% When designing a complex pixel-stream video processing algorithm, it is a
% good practice to develop a parallel reference design using functions from
% the Image Processing Toolbox(TM). These functions process full image
% frames. Such a reference design helps verify the implementation of
% the pixel-stream design by comparing the output image from the full-frame
% reference design to the output of the pixel-stream design.
%
% The function
% <matlab:edit(fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples','EnhancedEdgeDetectionHDLReference.m')) EnhancedEdgeDetectionHDLReference>
% contains a similar set of four functions as in the
% <matlab:edit(fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples','EnhancedEdgeDetectionHDLDesign.m')) EnhancedEdgeDetectionHDLDesign>.
% The key difference is that the functions from Image Processing Toolbox
% process full-frame data.
%
% Due to the implementation difference between |edge| function and
% visionhdl.EdgeDetector System object, reference and design output are
% considered matching if frmOut and frmRef differ in no greater than 20 pixels.
%% Create MEX File and Simulate the Design
% So as not to pollute your current working folder, execute the following
% lines of code to copy the necessary example files into a temporary folder.
currDir = pwd;
tempDir = tempname;
% Create a temporary folder and copy the MATLAB files.
mkdir(tempDir);
demoDir = fullfile(matlabroot,'toolbox','visionhdl','visionhdlexamples');
copyfile(fullfile(demoDir,'EnhancedEdgeDetectionHDLDesign.m'),tempDir);
copyfile(fullfile(demoDir,'EnhancedEdgeDetectionHDLViewer.m'),tempDir);
copyfile(fullfile(demoDir,'EnhancedEdgeDetectionHDLReference.m'),tempDir);
copyfile(fullfile(demoDir,'EnhancedEdgeDetectionHDLTestBench.m'),tempDir);
cd(tempDir);
%%
% Generate and execute the MEX file.
fprintf('Generating the MEX file, please wait ..\n');
codegen('EnhancedEdgeDetectionHDLTestBench');
fprintf('Executing the MEX file ..\n');
EnhancedEdgeDetectionHDLTestBench_mex;
%%
%
% <<visionhdlenhancededge_ml_viewer.png>>
%
% The upper video player displays the original color video on the left,
% and its noisy version after adding salt and pepper noise on the right.
% The lower video player, from left to right, represents: the
% grayscale image after color space conversion, the de-noised version after
% median filter, the edge output after edge detection, and the enhanced
% edge output after morphological closing operation.
%
% Note that in the lower video chain, only the enhanced edge output
% (right-most video) is generated from pixel-stream design. The other three
% are the intermediate videos from the full-frame reference design.
% To display all of the four videos from the pixel-stream
% design, you would have written the design file to output four sets of
% pixels and control signals, and instantiated three more
% *visionhdl.PixelsToFrame* objects to convert the three intermediate pixel
% streams back to frames. For the sake of simulation speed and the clarity
% of the code, this example does not implement the intermediate
% pixel-stream displays.
%% HDL Code Generation
% To create a new project, enter the following command in the temporary
% folder
%
% coder -hdlcoder -new EnhancedEdgeDetectionProject
%
% Then, add the file 'EnhancedEdgeDetectionHDLDesign.m' to the project as the MATLAB
% Function and 'EnhancedEdgeDetectionHDLTestBench.m' as the MATLAB Test Bench.
%
% Refer to
% <matlab:helpview(fullfile(docroot,'hdlcoder','examples','getting-started-with-matlab-to-hdl-workflow.html')) Getting Started with MATLAB to HDL Workflow>
% for a tutorial on creating and populating MATLAB HDL Coder projects.
%
% Launch the Workflow Advisor. In the Workflow Advisor, right-click the
% 'Code Generation' step. Choose the option 'Run to selected task' to
% run all the steps from the beginning through HDL code generation.
%
% Examine the generated HDL code by clicking the links in the log window.
%
% Run the following commands to clean up the temporary project folder.
clear mex;
cd(currDir);
rmdir(tempDir,'s');
clear currDir tempDir demoDir;
%%
% Copyright 2014 The MathWorks, Inc.
displayEndOfDemoMessage(mfilename)