含仿真录像，基于MSER和多尺度形态学分割的交通牌字符检测分割matlab仿真

clc; clear; close all; warning off; addpath(genpath(pwd)); P = imread('st10.jpg'); %B=imresize(colorImage,[,300]); I = rgb2gray(P); % Detecting MSER features using detectMSERfeartures function. [mserRegions, mserConnComp] = detectMSERFeatures(I, ... 'RegionAreaRange',[200 8000],'ThresholdDelta',4); figure imshow(I) hold on plot(mserRegions, 'showPixelList', true,'showEllipses',false) title('MSER regions') hold off % Measuring the MSER properties mserStats = regionprops(mserConnComp, 'BoundingBox', 'Eccentricity', ... 'Solidity', 'Extent', 'Euler', 'Image'); % Calculating the aspect ratio using bounding box. bbox = vertcat(mserStats.BoundingBox); w = bbox(:,3); h = bbox(:,4); aspectRatio = w./h; % DeterminIng which regions to remove. filterregions = aspectRatio' > 3; filterregions = filterregions | [mserStats.Eccentricity] > .995 ; filterregions = filterregions | [mserStats.Solidity] < .3; filterregions = filterregions | [mserStats.Extent] < 0.2 | [mserStats.Extent] > 0.9; filterregions = filterregions | [mserStats.EulerNumber] < -4; % Remove regions mserStats(filterregions) = []; mserRegions(filterregions) = []; figure imshow(I) hold on plot(mserRegions, 'showPixelList', true,'showEllipses',false) title('After Removing Non-Text Regions Based On Geometric Properties') hold off % zero padding and binarization regionImage = mserStats(6).Image; regionImage = padarray(regionImage, [1 1]); % Compute the stroke width image. imagedistance = bwdist(~regionImage); skeletonImage = bwmorph(regionImage, 'thin', inf); strokeWidthImage = imagedistance; strokeWidthImage(~skeletonImage) = 0; % Show the region image alongside the stroke width image. figure subplot(1,2,1) imagesc(regionImage) title('Region Image') subplot(1,2,2) imagesc(strokeWidthImage) title('Stroke Width Image') % stroke width variation metric strokeWidthValues = imagedistance(skeletonImage); strokeWidthMetric = std(strokeWidthValues)/mean(strokeWidthValues); % stroke width variation metric strokeWidthThreshold = 0.4; strokeWidthFilterIdx = strokeWidthMetric > strokeWidthThreshold; % Processing the remaining regions for j = 1:numel(mserStats) regionImage = mserStats(j).Image; regionImage = padarray(regionImage, [1 1], 0); imagedistance = bwdist(~regionImage); skeletonImage = bwmorph(regionImage, 'thin', inf); strokeWidthValues = imagedistance(skeletonImage); strokeWidthMetric = std(strokeWidthValues)/mean(strokeWidthValues); strokeWidthFilterIdx(j) = strokeWidthMetric > strokeWidthThreshold; end % Remove regions based on the stroke width variation mserRegions(strokeWidthFilterIdx) = []; mserStats(strokeWidthFilterIdx) = []; % Show remaining regions figure imshow(I) hold on plot(mserRegions, 'showPixelList', true,'showEllipses',false) title('After Removing Non-Text Regions Based On Stroke Width Variation') hold off % Get bounding boxes for all the regions bboxes = vertcat(mserStats.BoundingBox); xmin = bboxes(:,1); ymin = bboxes(:,2); xmax = xmin + bboxes(:,3) - 1; ymax = ymin + bboxes(:,4) - 1; % Expanding the bounding boxes %expansionamount=0.004; expansionAmount = 0.017; xmin = (1-expansionAmount) * xmin; ymin = (1-expansionAmount) * ymin; xmax = (1+expansionAmount) * xmax; ymax = (1+expansionAmount) * ymax; xmin = max(xmin, 1); ymin = max(ymin, 1); xmax = min(xmax, size(I,2)); ymax = min(ymax, size(I,1)); % Showing the expanded bounding boxes expandedBBoxes = [xmin ymin xmax-xmin+1 ymax-ymin+1]; IExpandedBBoxes = insertShape(P,'Rectangle',expandedBBoxes,'LineWidth',3); figure imshow(IExpandedBBoxes) title('Expanded Bounding Boxes Text') % Compute the overlap ratio overlapRatio = bboxOverlapRatio(expandedBBoxes, expandedBBoxes); % simplify the graph representation. n = size(overlapRatio,1); overlapRatio(1:n+1:n^2) = 0; g = graph(overlapRatio); % Finding the connected text regions componentIndices = conncomp(g); % Merging the boxes xmin = accumarray(componentIndices', xmin, [], @min); ymin = accumarray(componentIndices', ymin, [], @min); xmax = accumarray(componentIndices', xmax, [], @max); ymax = accumarray(componentIndices', ymax, [], @max); text = [xmin ymin xmax-xmin+1 ymax-ymin+1]; numRegionsInGroup = histcounts(componentIndices); text(numRegionsInGroup == 1, :) = []; % Show the final text detection result. ITextRegion = insertShape(P, 'Rectangle', text,'LineWidth',3); figure imshow(ITextRegion) title('Detected Text') ocrtxt = ocr(I, text); [ocrtxt.Text]