如何使用单元阵列图或存储数据到数组准备策划?

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塔克伟业 2021年7月19日

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这个问题直接联系

https://es.mathworks.com/matlabcentral/answers/881858-how-to-plot-graph-using-cell-array-or-store-the-data-into-array-to-prepare-it-for-plotting

评论道: 塔克伟业2021年7月20日

你好,我将数据存储到单元阵列(这是z 埃塔{我IntDiff_no Noise_no}) 有困难,把它们分成小的单元阵列阴谋策划这样的图。有什么办法,或者我应该改变我数组,存储它们吗?但我不知道如何去做。下面附加的代码。希望得到指导解决这个问题。谢谢你！

                         %创建空白图像
                        
                         w = 200;
                        
                         h = 200;
                        
                         blankImage = 255 * 1 (w h, 3,“uint8”);
                        
                         %的位置在空单元的信
                        
                         position_x = (w + 1) / 2;
                        
                         position_y = (h + 1) / 2;
                        
                         %不同字体大小,从10到16
                        
                         font_start = 120;
                        
                         font_end = 160;
                        
                         num_fonts = font_start: 10: font_end;
                        
                         %得到字体的数量
                        
                         numImages =长度(num_fonts);
                        
                         %创建一个单元阵列的字体填写下一步的图像
                        
                         Output_collection =细胞(1、numImages);
                        
                         Orig_grayImage =细胞(1、numImages);
                        
                         alphabet_segmented =细胞(5 5 5);
                        
                         check_foreground =细胞(5 5 5);
                        
                         alphabet_Uppercase =细胞(1、26);
                        
                         alphabet_Uppercase = [“一个”,“B”,“C”,' D ',“E”,“F”,‘G’,“H”,“我”,“J”,“K”,“L”,“米”,“N”,“O”,“P”,“问”,“R”,“年代”,“T”,“U”,“V”,' W ',“X”,“Y”,“Z”];
                        
                         Int_image_array =细胞(1、numImages);
                        
                         =细胞(1、numImages);
                        
                         Binaryimg{1,} =细胞(1,numImages);
                        
                         alphabet_orginal =细胞(1、numImages);
                        
                         % alphabet_Image =细胞(26岁,5);
                        
                         noise_start = 0.01;
                        
                         noise_end = 0.05;
                        
                         num_noiseimg = noise_start: 0.01: noise_end;
                        
                         each_noise =长度(num_noiseimg);
                        
                         alphabetNoiseimg_collection =细胞(5 5 5);
                        
                         alphabetSauvImage_collection =细胞(5 5 5);
                        
                         真的= 0;
                        
                         noise_pos = 1;
                        
                         Int_image =细胞(1、numImages);
                        
                         IntimageFig_pos = 1:2:9;
                        
                         NoiseimgFig_pos = 2:2:10;
                        
                         intensityDifference = 20:20:100;
                        
                         each_intensityDifference =长度(intensityDifference);
                        
                         ζ=细胞(5 5 5);
                        
                         % for循环创建字母“A”
                        
                         %灰度
                        
                         %存储单元阵列
                        
                         % all_alphabet = 1:
                        
                         为我= 1:numImages
                        
                         为font_size = num_fonts(我)
                        
                         Orgimage = insertText (blankImage [position_x position_y),“一个”,“字体”,“Times New Roman”,“字形大小”font_size,“输入TextColor”,“黑”,“BoxColor”,' w ',“BoxOpacity”0,“AnchorPoint”,“中心”);
                        
                         grayImage = rgb2gray (Orgimage);
                        
                         BWImage = imcomplement (grayImage);
                        
                         {1,}= BWImage;
                        
                         Orig_grayImage {1,} = {1,};
                        
                         Binaryimg {1,} = imbinarize (Orig_grayImage {1,});
                        
                         alphabet_orginal{1,} =总和(Binaryimg {1,} (:));
                        
                         %图(我);
                        
                         % imshow ({1,});
                        
                         % impixelinfo;
                        
                         %背景= BWImage = = 0;
                        
                         %前景= ~背景;
                        
                         % Newforegnd =前景;
                        
                         b = insertText (blankImage [position_x position_y),“b”,“字体”,“Times New Roman”,“字形大小”font_size,“输入TextColor”,“黑”,“BoxColor”,' w ',“BoxOpacity”0,“AnchorPoint”,“中心”);
                        
                         o = insertText (blankImage [position_x position_y),“o”,“字体”,“Times New Roman大胆”,“字形大小”font_size,“输入TextColor”,“黑”,“BoxColor”,' w ',“BoxOpacity”0,“AnchorPoint”,“中心”);
                        
                         BWImage_bin = imbinarize (BWImage);
                        
                         = repmat (“b”、大小(BWImage_bin));
                        
                         BoldO =“<强> o < / >强”;
                        
                         (BWImage_bin) =“o”;
                        
                         显示(出);
                        
                         Output_collection {1,} =;
                        
                         %次要情节(5 1我);
                        
                         % imshow (BWImage);
                        
                         %轴上;
                        
                         %的标题(sprintf (% d '的字体大小,font_size));
                        
                         为IntDiff_no = 1: each_intensityDifference
                        
                         为IntDiff_percentage = intensityDifference (IntDiff_no)
                        
                         % backgroundGrayLevel = IntDiff_percentage;
                        
                         % Int_image = {1,};
                        
                         % background_range = {1,} = = 0;
                        
                         % Int_image (background_range) = backgroundGrayLevel;
                        
                         % foregroundGrayLevel = backgroundGrayLevel + ((backgroundGrayLevel / 100) * 255);
                        
                         % foreground_range = {1,} = = 255;
                        
                         % Int_image (foreground_range) = foregroundGrayLevel;
                        
                         % Int_image_array{我IntDiff_no} = Int_image;
                        
                         highIntensity = (IntDiff_percentage / 100) * 255;% 20%
                        
                         Int_image = uint8(重新调节({1,},0,highIntensity));
                        
                         Int_image_array{我IntDiff_no} = Int_image;
                        
                         图(“名字”sprintf (% d为高斯噪声的字体大小font_size),“NumberTitle”,“关闭”);
                        
                         为Noise_no = 1: each_noise
                        
                         为噪音= num_noiseimg (Noise_no)
                        
                         %应用Gaussiannoise字母,
                        
                         %使用0.01到0.05(每一步increament 0.01)标准差
                        
                         NoiseImg = imnoise (Int_image_array{我IntDiff_no},“高斯”,0,噪音);
                        
                         alphabetNoiseimg_collection{我IntDiff_no Noise_no} = NoiseImg;
                        
                         %应用sauvola的阈值
                        
                         % m是平均值
                        
                         % k是一个常数在0.2 - 0.5%之间
                        
                         % s是标准差
                        
                         % R是灰度
                        
                         %图(“名字”,sprintf(字母字体大小% d的形象,font_size),“NumberTitle”,“关闭”);
                        
                         % S = m * (1 + k * (S / R - 1));
                        
                         % R = 128;
                        
                         % k = 0.2;
                        
                         sauvImage = sauvola (NoiseImg (150 150));
                        
                         alphabetSauvImage_collection{我IntDiff_no Noise_no} = sauvImage;
                        
                         %检查总形象
                        
                         流(“我是% d”,我);
                        
                         % imshow (sauvImage);
                        
                         %图(“名字”、“Sauvola阈值性能试验后”,“NumberTitle”,“关闭”);
                        
                         Image_segmented = nnz (sauvImage)
                        
                         alphabet_segmented{我IntDiff_no Noise_no} = Image_segmented;
                        
                         check_foreground{我IntDiff_no Noise_no} =总和(sauvImage (:))
                        
                         ζ{我IntDiff_no Noise_no} = alphabet_orginal {1,} / alphabet_segmented{我IntDiff_no Noise_no};
                        
                         如果alphabet_segmented{我IntDiff_no Noise_no} = = check_foreground{我IntDiff_no Noise_no}
                        
                         真的= true + 1;
                        
                         结束
                        
                         次要情节(5、1、Noise_no);
                        
                         imshow (alphabetNoiseimg_collection{我IntDiff_no Noise_no});
                        
                         轴在;
                        
                         标题(sprintf (的高斯噪声性病dev % f和强度差异% f '、噪音、IntDiff_percentage));
                        
                         结束
                        
                         结束
                        
                         结束
                        
                         结束
                        
                         图(“名字”sprintf (% d强度不同的字体大小font_size),“NumberTitle”,“关闭”);
                        
                         为int_no = 1: IntDiff_no
                        
                         次要情节(5、1、int_no);
                        
                         imshow (Int_image_array{我int_no});
                        
                         轴在;
                        
                         标题(sprintf (“字母强度差异% d %”intensityDifference (int_no)));
                        
                         结束
                        
                         结束
                        
                         结束
                        
                         流(“% d sauvola形象”,真正的);
                        
                         图(“名字”,“图像不同font_size”,“NumberTitle”,“关闭”);
                        
                         为font_no = 1: numImages
                        
                         为each_font = num_fonts (font_no)
                        
                         次要情节(5、1、font_no);
                        
                         imshow (Orig_grayImage {1, font_no});
                        
                         轴在;
                        
                         标题(sprintf (“图像% d字体大小”each_font));
                        
                         结束
                        
                         结束
                        
                         图(“名字”,“Sauvola阈值”,“NumberTitle”,“关闭”);
                        
                         为font_size = num_fonts(我)
                        
                         为IntDiff_no = 1: each_intensityDifference
                        
                         为IntDiff_percentage = intensityDifference (IntDiff_no)
                        
                         为Noise_no = 1: each_noise
                        
                         为噪音= num_noiseimg (Noise_no)
                        
                         次要情节(5、1、Noise_no);
                        
                         imshow (alphabetSauvImage_collection{我IntDiff_no Noise_no});
                        
                         标题(sprintf (的图像% d字体大小,% f强度差异,% d噪音',IntDiff_percentage font_size噪音));
                        
                         结束
                        
                         结束
                        
                         结束
                        
                         结束
                        
                         结束