基于颜色的图像内容检索MATLAB实现

% 这是主文件，计算给定图像的直方图，然后根据数据返回相似的图像。 % 调用方法 searchImageHist('redflower.jpg', 'model1Hist', 11); function searchImageHist(imageName, modelName, nResults) % function searchImageHist(imageName, modelName, nResults) % Image retrieval m-file % nResults % % % % nResults=15 % load train model: load('f:\imQuery\mydatefiledownload'); load('f:\imQuery\model1Hist'); %必须导入 % compute 3-D image histograms (HSV color space): fprintf('Computing 3D (HSV) histogram for query image...\n'); [Hist, RGBQ] = getImageHists('D:\download\601.jpg'); % number of training samples: Nfiles = length(Hists); % decision thresholds: t = 0.010; t2 = 0.8; fprintf('Searching...\n'); range = 0.0:0.1:1.0; rangeNew = 0.0:0.05:1.0; [x,y,z] = meshgrid(range); [x2,y2,z2] = meshgrid(rangeNew); Hist = interp3(x,y,z,Hist,x2,y2,z2); Similarity = zeros(Nfiles, 1); for (i=1:Nfiles) % for each file in database: % compute (normalized) eucledean distance for all hist bins: HistT = interp3(x,y,z,Hists{i},x2,y2,z2); DIFF = abs(Hist-HistT) ./ Hist; % keep distance values for which the corresponding query image's values % are larger than the predefined threshold: DIFF = DIFF(Hist>t); % keep error values which are smaller than 1: DIFF2 = DIFF(DIFF<t2); L2 = length(DIFF2); % compute the similarity meaasure: Similarity(i) = length(DIFF) * mean(DIFF2) / (L2^2); % (interface): plot images with small similarity measures: plotThres = 0.5 * 10 / length(DIFF); if (Similarity(i) < plotThres) % fprintf('%70s %5.2f %5d %5d\n', files{i}, median(DIFF2), % length(DIFF), L2); subplot(2,2,1);imshow(RGBQ); title('Query image'); RGB = imread(files{i}); subplot(2,2,2);imshow(RGB); title('A similar image ... Still Searching ...'); subplot(2,2,3); plot(DIFF) if (length(DIFF2)>1) subplot(2,2,4); plot(DIFF2); axis([1 length(DIFF2) 0.2 1]) end drawnow end end % find the nResult "closest" images: [Sorted, ISorted] = sort(Similarity); NRows = ceil((nResults+1) / 3); % plot query image: subplot(NRows,3,1); imshow(RGBQ); title('Query Image'); % ... plot similar images: for (i=1:nResults) RGB = imread(files{ISorted(i)}); str = sprintf('Im %d: %.3f',i,100*Sorted(i)); subplot(NRows,3,i+1); imshow(RGB); title(str); end fprintf('Done\n');