Questions tagged [optical-character-recognition]

For questions about the application of AI/ML algorithms in the field of optical character recognition (OCR), aka optical character reader (OCR), which is the mechanical or electronic conversion of images of typed, handwritten, or printed text into machine-encoded text.

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Is this a good implementation of this LSTM architecture?

I had been looking at some OCR problems and came across this presentation. I implemented it. In the presentation, there is the LSTM-Stack (diagram and algorithm, slide 32): Here is a visualization of ...
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26 views

Machine Learning Algorithm for OCR on full pages of text

I would like to build an OCR application. In. particular, I want my algorithm to scan entire pages of text in a specific niche language. I was therefore wondering if there are some algorithms that ...
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1answer
56 views

Which AI techniques are there that combine multiple models to make sense of data at different stages?

I have been working to design a system that uses multiple machine learning models to make sense of data that is dynamically webscraped. Each AI would handle a specific task, for example: An AI model ...
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1answer
103 views

Why object detection algorithms are poor in optical character recognition?

OCR is still a very hard problem. We don't have universal powerful solutions. We use the CTC loss function An Intuitive Explanation of Connectionist Temporal Classification | Towards Data Science ...
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1answer
150 views

In OCR, how should I deal with the warped text on the sides of oval objects?

Consider an image that contains one can (or bottle, or any similar oval object), which has texts all over it. In the image below, I have many bottles, but you can assume that each image only contains ...
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1answer
51 views

What are the disadvantages to using a distance metric in character recognition prediction

I am reading this paper, that is discussing the use of distance metrics for character recognition predicton. I can see the advantages of using a distance metrics in predictions like character ...
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1answer
79 views

Can a convolutional neural network classify text document images?

I know convolutional neural networks are commonly used for image recognition, but I was wondering if they would be able to distinguish between predominantly text-based documents vs something like ...
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26 views

Is it possible to automatically remove ignore (or remove) the equations (and other noisy elements) while performing OCR?

I have academic pdf data. I am using OCR for converting it into text format. The pdf has a few mathematical equations and terms which are acting as noise for my task. Any way through which the task of ...
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1answer
34 views

Detect data in tables of roughly the same structure

I would like to train a model that serializes a table of nutrition facts into it's values. The tables can vary in form and colour, but always contain the same set of keys (e.g. carbs, fats). Examples ...
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1answer
119 views

How should I define the loss function for a multi-object detection problem?

I'm trying to create a text recognition project using CNN. I need help regarding the text detection task. I have the training images and bounding box details for them. But I'm unable to figure out ...
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41 views

OCR - Text recognition from Image

I plan to develop OCR application using tensorflow to get the value from the image. Text in the image may handwritting or text printed. From the image, my ocr appplication will able to get the value ...
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1answer
90 views

How can I detect diagram region and extract (crop) it from a research paper [closed]

How can I detect diagram region and extract(crop) it from a research paper
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126 views

How can I recognise the name of a molecule given an image of its structure?

I want to recognize the name of the chemical structure from the image of the chemical structure. For example, in the image below, it is a benzene structure, and I want to recognize that it is benzene ...
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82 views

Is there a deep learning-based architecture for digit localisation?

I'm new to object detectors and segmentation. I want to localize digits on a plate as fast as possible. All images of the dataset are normalized to $300 \times 60$. There are different approaches to ...
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1answer
89 views

Generate credit cards dataset for locating number region

Currently I'm working on a project for scanning credit card and text extraction from cards. So first of all I decided to preprocess my images with some filters like thresholding, dilation and some ...
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1answer
126 views

Is there any way to classify Document Image without OCR?

I have multiple invoices images which need to classify invoice types such as fright, utility, goods, etc. Is there any way to classify without OCR?
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68 views

An approach on reading musical notes from photos

I was looking around, a promising approach was this: https://github.com/mpralat/notesRecognizer the problem is: it doesn't seem good enough. One should be able to read musical notes with lower ...
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2answers
79 views

Attempting to solve a optical character recognition task using a feed-forward network

I am doing some experimentation on neural networks, and for that I am trying to program a plain OCR task. I have learned CNNs are the best choice ,but for the time being and due to my inexperience, I ...
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0answers
41 views

How does a neural network output text box location data?

I'm interested in creating a convolutional neural network or LSTM to locate text in an image. I don't want to OCR the text yet, just find the text regions. Yes, I know Tesseract and other systems can ...
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2answers
627 views

Is it possible to use AI to denoise noised or 'dirty' documents?

I have some documents containing some text (machine writing text) that I intend to apply OCR on them in order to extract the text. The problem is that these documents contain a lot of noise but in ...
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0answers
75 views

zonal or template ocr invoices reading

I'd like to explore the possibilities of applying artificial intelligence to ocr reading. Basic ocr invoices processing let me convert 30% of them only. The main purpose is defining invoices areas by ...
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1answer
48 views

How much extra information can we conclude from a neural network output values?

Consider I have a 3 layers neural network. Input Layer containing 784 neurons. Hidden layer containing 100 neurons. Output layer containing 10 neurons. My objective is to make an OCR and I used ...
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2answers
784 views

How could I use machine learning to detect text and non-text regions in scanned documents?

I have a collection of scanned documents (which come from newspapers, books, and magazines) with complex alignments for the text, i.e. the text could be at any angle w.r.t. the page. I can do a lot of ...
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2answers
2k views

Effective algorithms for OCR

I am using Google's OCR to extract text from images, like receipts and invoices. Whare examples of techniques used to make sense of the text? For example, I would like to extract the date, name of the ...
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1answer
695 views

How can I use deep neural networks to recognize characters on vehicle license plate? [closed]

I was able to extract the license plate from a given car image, using Matlab. I would like to use deep neural networks to recognize the characters on the plate now. How can i proceed further? I don't ...
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3answers
6k views

Why can't OCR be perceived as a good example of AI?

On the Wikipedia page about AI, we can read: Optical character recognition is no longer perceived as an exemplar of "artificial intelligence" having become a routine technology. On the other hand, ...
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569 views

Are there any textual CAPTCHA challenges which can fool AI, but not human?

Are there any modern techniques of generating textual CAPTCHA (so person needs to type the right text) challenges which can easily fool AI with some visual obfuscation methods, but at the same time ...
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1answer
98 views

What are the challenges for recognising the handwritten characters?

This 2014 article saying that a Chinese team of physicists have trained a quantum computer to recognise handwritten characters. Why did they have to use a quantum computer to do that? Is it just for ...