• 【计算机视觉领域】常用的 feature 提取方法,feature 提取工具包


     

    【计算机视觉领域】常用的 feature 提取方法,feature 提取工具包

     

      利用 VL 工具包进行各种特征的提取:

      VL 工具包官网地址:http://www.vlfeat.org/index.html

     

    %% Extract Every kind of Features
    % the VL_tool box for feature extraction.
    clc;
    run('/home/wangxiao/Documents/MATLAB/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/vl_setup.m')
    imagePath = '/home/wangxiao/Documents/Sun-80-dataset/Sun_80_dataset/train_image_sun_256_256/' ;
    Labeled_data = importdata('/home/wangxiao/Documents/Sun-80-dataset/Sun_80_dataset/SUN100_Label_train_0.5_.txt');
    Unlabel_data = importdata('/home/wangxiao/Documents/Sun-80-dataset/Sun_80_dataset/SUN100_Unlabel_train_0.5_.txt');

    for i = 1:size(Labeled_data.data, 1)
    imageName = Labeled_data.textdata{i, 1};
    % image = imread([imagePath, imageName]);

    image = imread('/home/wangxiao/Pictures/wallhaven-382471.png');
    image = imresize(image, [224, 224]);
    % change the image into single precision.
    figure; imshow(image);
    imgs = im2single(rgb2gray(image)) ;

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %% use vl_covdet to compute and visualize co-variant features.

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    frames = vl_covdet(imgs, 'verbose') ;
    hold on ;
    vl_plotframe(frames) ; % visualize the features.

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %% use vl_hog to extract the hog feature.

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    cellSize = 8 ;
    hog = vl_hog(imgs, cellSize, 'verbose') ;
    imhog = vl_hog('render', hog, 'verbose') ;
    clf ; imagesc(imhog) ; colormap gray ;

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %% use vl_sift to extract the sift feature.

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    [f,d] = vl_sift(imgs) ;
    perm = randperm(size(f,2)) ;
    sel = perm(1:50) ;
    h1 = vl_plotframe(f(:,sel)) ;
    h2 = vl_plotframe(f(:,sel)) ;
    set(h1,'color','k','linewidth',3) ;
    set(h2,'color','y','linewidth',2) ;

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %% use vl_mser to extact the mser feature.

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    I = uint8(rgb2gray(image)) ;
    [r,f] = vl_mser(I,'MinDiversity',0.7,...
    'MaxVariation',0.2,...
    'Delta',10) ;
    f = vl_ertr(f) ;
    vl_plotframe(f) ;

    M = zeros(size(I)) ;
    for x=r'
    s = vl_erfill(I,x) ;
    M(s) = M(s) + 1;
    end
    figure(2) ;
    clf ; imagesc(I) ; hold on ; axis equal off; colormap gray ;
    [c,h]=contour(M,(0:max(M(:)))+.5) ;
    set(h,'color','y','linewidth',3) ;

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

    %% use vl_quickseg to execute Quick shift.

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

    I = uint8(rgb2gray(image));
    ratio = 0.5;
    kernelsize = 2;
    maxdist = 50;
    ndists = 10;
    Iseg = vl_quickseg(I, ratio, kernelsize, maxdist);
    Iedge = vl_quickvis(I, ratio, kernelsize, maxdist, ndists) ;
    imagesc(Iedge);
    axis equal off tight;
    colormap gray;

    end

     

     

      

     

     

     

     

     

     

     

     

     

     

     

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  • 原文地址:https://www.cnblogs.com/wangxiaocvpr/p/5752854.html
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