Questions tagged [ocr]

Optical character recognition (also optical character reader, OCR) is the mechanical or electronic conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo) or from subtitle text superimposed on an image (for example from a television broadcast).

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What are the methods possible for using Unicode for Optical Character Recognition( OCR) using Python? [on hold]

I would like to know on multiple ways on which i can use Unicode for OCR on images(.jpg and .png) using python to extract text. …
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Optical Character Recognition - digits on the screen

My task is to classify a digit based on a small image containing one digit only. The font type and size is the same across the training/test dataset, but the position of the digit in the image might ...
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How to feed feature map direct to Connectionist Temporal Classifier(CTC) in text recognition?

I am now developing an OCR system for my language. For architecture of the model, I am thinking of using Resnet-18 for feature extraction and then use CTC for loss function. My first approach is using ...
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Avoiding OCR performance coupling to upstream Bounding Box model

I have a model pipeline where I first use an object detection deep learning model to locate text regions in images of natural scenery (i.e. outdoor images), and then send the cropped region to a deep ...
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Is CTC Loss function right for License Plate Recognition?

I trained some CNN model for license plate recognition using stacked LSTM and convolutional layers, but I got stuck in %88 accuracy. (This accuracy is on the whole license plate not one character). ...
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What NN architecture to use for documents OCR?

I recently go interested in document OCR and would like to gather some opinions on what NN to use. I wonder if there are any proven examples that I can exploit? I have heard of CNN+LSTM+CTC is good ...
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An algorithm to read handwriting from checks

I've noticed that ATM machines have become very good at reading handwriting on checks. I would like to write a program (using some appropriate machine learning or computer vision library) that is ...
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KNN outperforms CNN

Disclaimer: I am a programmer by trade, not a statistician, so please cater to my ignorance when explaining things and I apologize now if I make any incorrect assumptions Please consider the ...
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Recognizing several digits in an image - CNN

I am attempting to build a convolution neural network that will learn to classify images that contain up to three digits. I am currently building my training labels with the following format: For ...
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Simple OCR over individual words from a fixed dictionary

I have a series of images, each containing a single word from a known dictionary of 2048 words. The size, font, and position of the word is known ahead of time, and I simply need to tell which word ...
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443 views

Automatically determine whether a form filled in by hand and then scanned is valid

I'd like to automatically determine whether a form which is filled in by hand and then scanned or photographed is "valid". To be considered valid, the form has to satisfy the following two criteria: ...
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671 views

Can CNN detect text in arbitrary position of image?

My task is that: there are some text in some position (left, right, top, bottom center, etc) of an images. The style (include size, orientation, font, etc) of text is arbitrary and the content length ...
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Train Neural Network For Handwritten Chinese Characters

The article here: http://novanoid.github.io/2014/09/26/training-a-neural-network-to-recognize-handwritten-digits/ discusses and implements a way to recognize handwritten digits. For images with a ...
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Normalizing features that represent the same thing

I'm working through the beginner exercise of classifying the MNIST dataset (recognizing hand written digits). If I train with 80% of the dataset, then test the remaining 20% of the samples, I get ~90% ...
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State-of-the-art ensemble learning algorithm in pattern recognition tasks?

The structure of this question is as follows: at first, I provide the concept of ensemble learning, further I provide a list of pattern recognition tasks, then I give examples of ensemble learning ...
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How many samples do I need for OCR problems?

I am thinking about collecting samples of hand written digits (0 to 9) from people. I'll try to test different algorithms for optimal character recognition- some form of neural network and random ...
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SVM Classifier with HOG Features

I am interested in having a system to detect and recognize speed limits from traffic signs. The detection part works fine, meaning that I am able to detect them inside any image. Now I would like to ...
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How is prior knowledge of letter/word patterns incorporated into handwriting (or speech) recognition?

Using handwriting recognition as an example, we can train various models to recognise individual characters but to actually be useful we must incorporate prior knowledge of common character sequences, ...
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How to remove horizontal bar in Hindi word Matlab

I wish to remove the horizontal bar (Shirorekha) from the word to get characters from the following image, for character recognition. Any ideas as to how can I do that. I tried to use Hough ...
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How can you use HMMs and ANNs for on-line handwriting recognition?

I've asked this question on cs.stackexchange before. It has a 20-hours remaining bounty there. On-line handwriting recognition is the task of converting a series of $(x(t),y(t))$ coordinates to ...