【答题卡识别】基于hough变换答题卡判定与成绩统计含Matlab源码

function [score,I4,I5] = SimplePaper_Inspection( filename) %输入参数： %filenames——包含需要判定的答题卡文件名 %读取图像 I = imread(filename); %预处理 I1 = Image_Normalize(I, 1 ); %平滑处理，模板尺寸[ 3 3 ]，sigma角 0 . 5 ，平滑方式：高斯滤波 hsize = [ 3 3 ]; sigma = 0 . 5 ; I2 = Image_Smooth(I1, hsize, sigma, 1 ); %灰度化 I3 = Gray_Convert(I2, 1 ); %二值化 bw2 = Image_Binary(I3, 1 ); %hough变换 [~, ~, xy_long] = Hough_Process(bw2, I1, 1 ); %变换斜率 angle = Compute_Angle(xy_long); %图像旋转 [I4, bw3] = Image_Rotate(I1, bw2, angle* 1.8 , 1 ); %形态学滤波 [bw4, Loc1] = Morph_Process(bw3, 1 ); %hough检测区域分界线 [Len, XYn, xy_long] = Hough_Process(bw4, I4, 1 ); %区域分割 [bw5, bw6] = Region_Segmation(XYn, bw4, I4, 1 ); %区域标记 [stats1, stats2, Line] = Location_Label(bw5, bw6, I4, XYn, Loc1, 1 ); %区域分析 [Dom, Aom, Answer, Bn] = Analysis(stats1, stats2, Line, I4); savefigure12img( ’t.jpg’ ); I5=imread( ’t.jpg’ ); %成绩判定 score=jieguo(bw5); fprintf( ’选择题得分为%d’ ,score);%在command窗口输出成 %将答题卡图片转存到results文件夹 Write_Results(); function I1 = Image_Normalize(I, flag) if nargin < 2 flag = 1 ; end if size(I, 1 ) > 2000 I = imresize(I, 0 . 2 , ’bilinear’ ); end I1 = imadjust(I, [ 0 0 . 6 ], [ 0 1 ]); if flag figure( 1 ); subplot( 2 , 1 , 1 ); imshow(I, []); title( ’原图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 1 , 2 ); imshow(I1, []); title( ’归一化图像’ , ’FontWeight’ , ’Bold’ ); end end function I2 = Image_Smooth(I1, hsize, sigma, flag) if nargin < 4 flag = 1 ; end if nargin < 2 hsize = [ 3 3 ]; sigma = 0 . 5 ; end h = fspecial( ’gaussian’ , hsize, sigma); I2 = imfilter(I1, h, ’replicate’ ); if flag figure( 2 ); subplot( 2 , 1 , 1 ); imshow(I1, []); title( ’平滑前图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 1 , 2 ); imshow(I2, []); title( ’平滑后图像’ , ’FontWeight’ , ’Bold’ ); end end function I1 = Gray_Convert(I, flag) if nargin < 2 flag = 1 ; end if ndims(I) == 3 I1 = rgb2gray(I); else I1 = I; end if flag figure( 3 ); subplot( 2 , 1 , 1 ); imshow(I, []); title( ’RGB图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 1 , 2 ); imshow(I1, []); title( ’灰度图像’ , ’FontWeight’ , ’Bold’ ); end end function bw2 = Image_Binary(I, flag) if nargin < 2 flag = 1 ; end bw1 = imbinarize(I, graythresh(I)); bw2 = ~bw1; if flag figure( 4 ); subplot( 1 , 3 , 1 ); imshow(I, []); title( ’待处理图像’ , ’FontWeight’ , ’Bold’ ); subplot( 1 , 3 , 2 ); imshow(bw1, []); title( ’二值化图像’ , ’FontWeight’ , ’Bold’ ); subplot( 1 , 3 , 3 ); imshow(bw2, []); title( ’二值化反色图像’ , ’FontWeight’ , ’Bold’ ); end end function [Len, XYn, xy_long] = Hough_Process(bw, Img, flag) if nargin < 3 flag = 1 ; end [H, T, R] = hough(bw); P = houghpeaks(H, 4 , ’threshold’ , ceil( 0 . 3 *max(H( : )))); lines = houghlines(bw, T, R, P, ’FillGap’ , 50 , ’MinLength’ , 7 ); max_len = 0 ; for k = 1 : length(lines) xy = [lines(k).point1; lines(k).point2]; len = norm(lines(k).point1-lines(k).point2); Len(k) = len; if len > max_len max_len = len; xy_long = xy; end XY{k} = xy; % 存储信息 end [Len, ind] = sort(Len( : ), ’descend’ ); % 按长度排序 % 直线信息排序 for i = 1 : length(ind) XYn{i} = XY{ind(i)}; end xy_long = XYn{ 1 }; x = xy_long( : , 1 ); y = xy_long( : , 2 ); if abs(diff(x)) < abs(diff(y)) x = [mean(x); mean(x)]; else y = [ 0 . 7 *y( 1 )+ 0 . 3 *y( 2 ); 0 . 3 *y( 1 )+ 0 . 7 *y( 2 )]; end xy_long = [x y]; if flag figure( 5 ); subplot( 1 , 2 , 1 ); imshow(bw); title( ’二值图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 2 , 2 ); imshow(H, [], ’XData’ , T, ’YData’ , R, ’InitialMagnification’ , ’fit’ ); xlabel( ’ heta’ ); ylabel( ’ho’ ); axis on; axis normal; title( ’霍夫变换域’ , ’FontWeight’ , ’Bold’ ) figure( 6 ); subplot( 1 , 2 , 1 ); imshow(Img); title( ’原图像’ , ’FontWeight’ , ’Bold’ ); subplot( 1 , 2 , 2 ); imshow(Img); title( ’区域标识图像’ , ’FontWeight’ , ’Bold’ ); hold on; plot(xy_long( : , 1 ), xy_long( : , 2 ), ’LineWidth’ , 2 , ’Color’ , ’r’ ); end end function angle = Compute_Angle(xy_long) x1 = xy_long( : , 1 ); y1 = xy_long( : , 2 ); K1 = -(y1( 2 )-y1( 1 ))/(x1( 2 )-x1( 1 )); angle = atan(K1)* 180 /pi; end function [I1, bw1] = Image_Rotate(I, bw, angle, flag) if nargin < 4 flag = 1 ; end I1 = imrotate(I, - 90 -angle, ’bilinear’ ); bw1 = imrotate(bw, - 90 -angle, ’bilinear’ ); if flag figure( 7 ); subplot( 2 , 2 , 1 ); imshow(I, []); title( ’原图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 2 , 3 ); imshow(bw, []); title( ’原二值图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 2 , 2 ); imshow(I1, []); title( ’校正图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 2 , 4 ); imshow(bw1, []); title( ’校正二值图像’ , ’FontWeight’ , ’Bold’ ); end end function [bw2, Loc] = Morph_Process(bw1, flag) if nargin < 2 flag = 1 ; end bw2 = bwareaopen(bw1, round( 0 . 005 *numel(bw1)/ 100 )); bws = sum(bw2); inds = find(bws>round(sum(bw2( : ))* 0 . 015 )); Loc = inds( 1 )- 5 ; bw2( : , Loc: end ) = 0 ; bw2 = bwareaopen(bw2, round( 0 . 005 *numel(bw1)/ 100 )); if flag figure( 8 ); subplot( 1 , 2 , 1 ); imshow(bw1, []); title( ’待操作图像’ , ’FontWeight’ , ’Bold’ ); subplot( 1 , 2 , 2 ); imshow(bw2, []); title( ’滤波图像’ , ’FontWeight’ , ’Bold’ ); end end function [bw1, bw2] = Region_Segmation(XY, bw, Img, flag) if nargin < 4 flag = 1 ; end for i = 1 : 2 xy = XY{i}; XY{i} = [ 1 xy( 1 , 2 ); size(bw, 2 ) xy( 2 , 2 )]; ri(i) = round(mean([xy( 1 , 2 ) xy( 2 , 2 )])); end minr = min(ri); maxr = max(ri); bw1 = bw; bw2 = bw; bw1( 1 :minr+ 5 , : ) = 0 ; bw1(maxr- 5 :end , : ) = 0 ; bw2(minr- 5 :end , : ) = 0 ; bw2( 1 :round (minr* 0 . 5 ), : ) = 0 ; if flag figure( 9 ); subplot( 2 , 2 , 1 ); imshow(Img, []); title( ’原图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 2 , 2 ); imshow(bw, []); title( ’原二值图像’ , ’FontWeight’ , ’Bold’ ); hold on; for i = 1 : 2 xy = XY{i}; plot(xy( : , 1 ), xy( : , 2 ), ’r-’ , ’LineWidth’ , 2 ); end hold off; subplot( 2 , 2 , 3 ); imshow(bw1, []); title( ’下区域图像’ , ’FontWeight’ , ’Bold’ ); subplot( 2 , 2 , 4 ); imshow(bw2, []); title( ’上区域图像’ , ’FontWeight’ , ’Bold’ ); end end function [stats1, stats2, Line] = Location_Label(bw1, bw2, Img, XYn, Loc1, flag) if nargin < 6 flag = 1 ; end [L1, num1] = bwlabel(bw1); stats1 = regionprops(L1); [L2, num2] = bwlabel(bw2); stats2 = regionprops(L2); Line1 = XYn{ 1 }; Line2 = XYn{ 2 }; if mean(Line2( : , 2 )) < mean(Line1( : , 2 )) Line1 = XYn{ 2 }; Line2 = XYn{ 1 }; end [r1, c1] = find(bw1); [r2, c2] = find(bw2); Loc2 = min([min(c1), min(c2)])- 5 ; Line1 = [ 1 mean(Line1( : , 2 )); size(Img, 2 ) mean(Line1( : , 2 ))]; Line2 = [ 1 mean(Line2( : , 2 )); size(Img, 2 ) mean(Line2( : , 2 ))]; Line3 = [Loc2 1 ; Loc2 size(Img, 1 )]; Line4 = [Loc1 1 ; Loc1 size(Img, 1 )]; Line{ 1 } = Line1; Line{ 2 } = Line2; Line{ 3 } = Line3; Line{ 4 } = Line4; if flag figure( 10 ); imshow(Img, []); title( ’标记图像’ , ’FontWeight’ , ’Bold’ ); hold on; for i = 1 : num1 temp = stats1(i).Centroid; plot(temp( 1 ), temp( 2 ), ’r.’ ); end hold off; set(gcf); end end function [Dom, Aom, Answer, Bn] = Analysis(stats1, stats2, Line, Img, flag) if nargin < 5 flag = 1 ; end Line1 = Line{ 1 }; Line2 = Line{ 2 }; Line3 = Line{ 3 }; Line4 = Line{ 4 }; yn1 = round(Line1( 1 , 2 ) + 0 . 18 *(Line2( 1 , 2 )-Line1( 1 , 2 ))); yn2 = round(Line1( 1 , 2 ) + 0 . 34 *(Line2( 1 , 2 )-Line1( 1 , 2 ))); yn3 = round(Line1( 1 , 2 ) + 0 . 50 *(Line2( 1 , 2 )-Line1( 1 , 2 ))); Linen1_1 = [Line1( 1 , 1 ) yn1; Line1( 2 , 1 ) yn1]; Linen2_1 = [Line1( 1 , 1 ) yn2; Line1( 2 , 1 ) yn2]; Linen3_1 = [Line1( 1 , 1 ) yn3; Line1( 2 , 1 ) yn3]; % 定位竖直网格分割线 xn1 = round(Line3( 1 , 1 ) + 0 . 22 *(Line4( 1 , 1 )-Line3( 1 , 1 ))); xn2 = round(Line3( 1 , 1 ) + 0 . 26 *(Line4( 1 , 1 )-Line3( 1 , 1 ))); xn3 = round(Line3( 1 , 1 ) + 0 . 48 *(Line4( 1 , 1 )-Line3( 1 , 1 ))); xn4 = round(Line3( 1 , 1 ) + 0 . 52 *(Line4( 1 , 1 )-Line3( 1 , 1 ))); xn5 = round(Line3( 1 , 1 ) + 0 . 73 *(Line4( 1 , 1 )-Line3( 1 , 1 ))); xn6 = round(Line3( 1 , 1 ) + 0 . 77 *(Line4( 1 , 1 )-Line3( 1 , 1 ))); xn7 = round(Line3( 1 , 1 ) + 0 . 98 *(Line4( 1 , 1 )-Line3( 1 , 1 ))); Linen1_2 = [xn1 Line3( 1 , 2 ); xn1 Line3( 2 , 2 )]; Linen2_2 = [xn2 Line3( 1 , 2 ); xn2 Line3( 2 , 2 )]; Linen3_2 = [xn3 Line3( 1 , 2 ); xn3 Line3( 2 , 2 )]; Linen4_2 = [xn4 Line3( 1 , 2 ); xn4 Line3( 2 , 2 )]; Linen5_2 = [xn5 Line3( 1 , 2 ); xn5 Line3( 2 , 2 )]; Linen6_2 = [xn6 Line3( 1 , 2 ); xn6 Line3( 2 , 2 )]; Linen7_2 = [xn7 Line3( 1 , 2 ); xn7 Line3( 2 , 2 )]; ym1_1 = round(Line1( 1 , 2 ) + 0 . 32 *(Linen1_1( 1 , 2 )-Line1( 1 , 2 ))); ym2_1 = round(Line1( 1 , 2 ) + 0 . 5 *(Linen1_1( 1 , 2 )-Line1( 1 , 2 ))); end