MATLAB: How to recognize negative numbers with OCR

computer visionComputer Vision Toolboxocr

I am using the following code to recognize numbers in images and transform it to values. However, it only recognizes positive values. Can you please help me to modify the code in order to be able to identify positive and negative values? Thanks in advance.

clc
clear all
close all
%%
I=imread('N1.png'); 
I2=I(:,:,3);
I3=ind2rgb(I2,gray);
I4=imcomplement(I3);
N=Im_text(I4);
function [val] = Im_text(Original) 
        % Increase image size by 3x
        my_image = imresize(Original, 3);
        % Localize words
        BW = imbinarize(rgb2gray(my_image));
        BW1 = imdilate(BW,strel('disk',6));
        s = regionprops(BW1,'BoundingBox');
        bboxes = vertcat(s(:).BoundingBox);
        % Sort boxes by image height
        [~,ord] = sort(bboxes(:,2));
        bboxes = bboxes(ord,:);
        % Pre-process image to make letters thicker
        BW = imdilate(BW,strel('disk',1));
        % Call OCR and pass in location of words. Also, set TextLayout to 'word'
        ocrResults = ocr(BW,bboxes,'CharacterSet','.0123456789','TextLayout','word');
        words = {ocrResults(:).Text}';
        words = deblank(words);
        val=str2double(words);
end

Best Answer

Can't you simply add a - to the CharacterSet? Then if the first character is a -, it's a negative number.

This works fine:

grayImage = imread('N1.png');
if ndims(grayImage) == 3
	grayImage = rgb2gray(grayImage);
end
imshow(grayImage, 'InitialMagnification', 400);
axis('on', 'image');
N = Im_text(grayImage)
caption = sprintf('The number in here is %f', N);
title(caption, 'FontSize', 20);
%==================================================================================
function [val] = Im_text(Original)
% Increase image size by 3x
my_image = imresize(Original, 3);
ocrResults = ocr(my_image, 'CharacterSet', '-.0123456789', 'TextLayout', 'line')
words = {ocrResults(:).Text}';
words = deblank(words);
val = str2double(words);
end

Related Solutions

MATLAB: Crop dark area and display the face only

Convert to grayscale and then threshold and find the bounding box

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
% Read in the color image.
folder = pwd;
baseFileName = 'm2.bmp';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 3, 1);
imshow(rgbImage, []);
axis on;
title('Original Color Image', 'FontSize', fontSize);
drawnow;
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Histogram the red channel, but there is a huge spike at 255 so let's not count those.
subplot(2, 3, 2);
grayImage = rgb2gray(rgbImage);
imshow(grayImage, []);
title('Gray Scale version', 'FontSize', fontSize);
subplot(2, 3, 3);
histogram(grayImage(grayImage<255))
grid on;
title('Histogram of Gray Scale Image', 'FontSize', fontSize);
someThresholdValue = 150;
binaryImage = grayImage > someThresholdValue;
% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);
subplot(2, 3, 4);
imshow(binaryImage);
grid on;
title('Binary Image', 'FontSize', fontSize);
% Label the binary image.
labeledImage = bwlabel(binaryImage);
props = regionprops(labeledImage, 'BoundingBox');
bbox = props.BoundingBox
croppedImageRGB = imcrop(rgbImage, bbox);
subplot(2, 3, 5);
imshow(croppedImageRGB);
grid on;
title('Cropped RGB Image', 'FontSize', fontSize);
% Gray scale version of cropped image
croppedImageGray = imcrop(grayImage, bbox);
subplot(2, 3, 6);
imshow(croppedImageGray);
grid on;
title('Cropped Gray Scale Image', 'FontSize', fontSize);

MATLAB: Ocr function doesn’t recognize the numbers

Hi,

A little bit of pre-processing and using ROIs to specify where the words are will help. By default, OCR uses page layout analysis to determine blocks of text. In this case, the image doesn't look like a normal page of text (like a PDF article for example).

To make it easier for OCR, first you can find the location of the words using regionprops and then pass the location of the words (as bounding boxes) to the OCR function. See the code below and results. They look accurate. You may have to play around more with the pre-processing to make this robust for a collection of different images. But hopefully, this gives you an idea on how to proceed:

capture = imread('Captura.PNG');
% Increase image size by 3x
my_image = imresize(capture, 3);
figure
imshow(my_image)
% Localize words
BW = imbinarize(rgb2gray(my_image));
BW1 = imdilate(BW,strel('disk',6));
s = regionprops(BW1,'BoundingBox');
bboxes = vertcat(s(:).BoundingBox);
% Sort boxes by image height
[~,ord] = sort(bboxes(:,2));
bboxes = bboxes(ord,:);
% Pre-process image to make letters thicker
BW = imdilate(BW,strel('disk',1));
% Call OCR and pass in location of words. Also, set TextLayout to 'word'
ocrResults = ocr(BW,bboxes,'CharacterSet','.0123456789','TextLayout','word');
words = {ocrResults(:).Text}';
words = deblank(words)

words =

39×1 cell array
    {'0'    }
    {'18.33'}
    {'0'    }
    {'14.23'}
    {'0'    }
    {'16.55'}
    {'0'    }
    {'15.65'}
    {'12.64'}
    {'14.77'}
    {'10.83'}
    {'13.79'}
    {'12.94'}
    {'12.55'}
    {'0'    }
    {'11.70'}
    {'9.84' }
    {'10.71'}
    {'9.74' }
    {'9.98' }
    {'9.33' }
    {'9.00' }
    {'7.22' }
    {'8.02' }
    {'7.45' }
    {'7.10' }
    {'6.56' }
    {'6.28' }
    {'5.86' }
    {'5.40' }
    {'5.02' }
    {'4.57' }
    {'4.10' }
    {'3.74' }
    {'3.39' }
    {'3.00' }
    {'2.71' }
    {'2.33' }
    {'2.08' }

Best Answer

Related Solutions

MATLAB: Crop dark area and display the face only

MATLAB: Ocr function doesn’t recognize the numbers

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