Questions tagged [ocr]

Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text.

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LSTM layer (keras) is causing all layers after it to constantly predict the same thing no matter the input

I have a model for OCR, which after 2-3 epochs gives the same output. When I predicted the values and looked at the output for each layer I realized that all layers after the 1st layer in the LSTM ...
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1k views

Extracting structure and content from invoices

Lately, I have been largely inspired by this https://rossum.ai/, which is able to extract text from invoice documents. Do you have any ideas on how this could be implemented? It's clear that they ...
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1answer
30 views

Context capturing in a Structured PDF?

I'm trying to extract resume (PDF) data. resumes always tend to follow a structure. so if you see some numbers in a cv; according to the context, we could tell whether its a telephone number, a ...
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1answer
149 views

Data set of vectors of SVG paths for digits

I have used the MNIST data set many times to train models for digit recognition based on object character recognition (OCR). I am now trying to do the same but with a data set of svg paths.. I am ...
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1answer
49 views

How to segment old digitized newspapers into articles

I'm working on a large corpus of french daily newspapers from the 19th century that have been digitized and where the data are in the form of raw OCR text files (one text file per day). In terms of ...
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34 views

Entity Linking for Receipts [closed]

I am building a model for reading receipts from their mobile snapshots. After the receipt is OCR'd, I plan to use a variation on LayoutLM for entity extraction. Entities are: "quantity", &...
2
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1answer
48 views

Does CRNN use sparse tensor value for its label?

I just read paper about cnn + rnn for text recognition. The labels of dataset is tensor of char index (e.g [0, 1, 2 ] for image with label "abc"). Since the label of each input has different length ...
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14 views

No gradients provided for any variable, when using Lambda to round model output

I have a problem where I need to predict some integers from an image. The problem is that this includes some negative integers too. I have done some reasearch and came accross Poisson which does count ...
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1answer
48 views

How to start with receipt OCR text detection

I'm thinking about an OCR system for digitalizing receipts. On the input system would take a picture of receipt and then return classified data (total_sum = Y, date = X, etc.). My question is ...
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711 views

What is the best approach to extract keys/values from documents?

I am thinking of training a model to automatically extract information from more or less structured documents like invoices. Here are the main challenges regarding this task: In fact, even though ...
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14 views

At which step we need to feed ground truth of transcription in CNN+RNN+CTC architecture(OCR) and in which format?

I have to recognize text from images and trying to understand CNN+BiLSTM+CTC architecture. I have text images in .jpg format but How should I generate its transcription like in .txt or in .xml format?...
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Are there any publicly available scan document database containing text together with ticked/unticked checkboxes?

I would like to train an optical mark recognition model (OMR) to detect and classify the ticked/unticked state of checkboxes in documents. Does anyone know where I can have access to a publicly ...
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32 views

How Does EAST detector implementation with VGG16 look? How many outputs does it have?

I was reading the Efficient and Accurate Scene Text Detector paper and saw the author reference VGG-16 as a possible stem "feature extractor" network. In the paper they say: In our ...
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71 views

Receipt fraud detection

I'm developing an OCR service that scans receipts and assigns points to user, based on amount of money spent. But the problem is that user can forge fake receipts and redeem them for extra points. ...
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1answer
154 views

Extracting text from few areas on product label

I'm trying to achieve algorithm that will extract text from few areas(marked with red color) on label(similar to attached image) and QR code on a single photo taken with mobile camera so label may be ...
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506 views

Character segmentation using deep learning

I'm developing a character segmentation algorithm for license plate OCR. My algorithm includes two steps: segmentation and recognition. There is almost no problem for recognition thanks to CNN. My ...
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18 views

Extracting and classifying information from images of semi-structured text

My problem statement is to identify and label the images of text in a particular type of document (say Deposit Slips). The document can have many different formats but they do not stray too far from ...
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56 views

Create a model that can extract only specific data out of receipts or invoices?

I'm trying to build a model that is capable of identifying only some of the information on receipts and invoices. All the documents having different structure in image format. Sample Data : Click here ...
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2answers
38 views

how can i detect medicine name and info(use and contents) by using medicine wrappers

I got one project idea creating a Cross-platform react-native app the project title is creating an app that can detect medicine name and other info from the medicine wrapper I'm thinking of using ...
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2answers
157 views

How to detect medicine name from the medicine wrapper

I have got medicine wrapper ( Packaging ) of different medicines. I want to detect medicine name out of it. I'm using Google Cloud Vision to extract all the text from the medicine wrapper. Text ...
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0answers
86 views

What is the difference between ICR and OCR?

I've just found the term "Intelligent Character Recognition" (ICR) on Wikipedia and other pages. According to Wikipedia: In computer science, intelligent character recognition (ICR) is an ...
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1answer
122 views

Can I train two stacked models end-to-end on different resolutions?

Is it possible to stack two networks on top of each other that operate on different resolutions of input data? So here's my usecase: like Google, I want to recognize text in images. Unlike Google, I ...
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2answers
2k views

What is the best approach for specified optical character recognition?

I have a quite understandable request of extracting information (invoice number, invoice data, due date, total etc.) from scanned invoices (the digital format is image, not PDF), preferably in Python. ...
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1answer
157 views

what is the loss function in char recognition using Tensorflow?

I have code in Tensorflow using convolution neural network to recognize the characters in street view Text (SVT) data. Since the label type is string, what should I use instead of ...
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88 views

Image segmentation network to extract questions from an image of a test paper?

This is the sample document -> I want to extract questions along with the options. There are other question papers as which have questions with diagrams in them. I want to be able to extract them ...
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25 views

Is there any research on zonal OCR / field level ORC / template OCR?

I've recently found the term "Zonal OCR": (source 1, 2, 3, 4). It seems to be essentially OCR, but restricted to relevant parts of the document. The interesting task about which I want to ...
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33 views

proper activation function at output and loss function to optimize for OCR?

I am trying to make a CNN model on IAM handwritten words data(which has images of words handwritten by multiple people and targets are text in the images). So, I can encode words to numbers(A=0, B=1 ...
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28 views

Possible?: Split pdf file on pages where object detection algorithm finds custom object

I have scanned documents in large pdf files consisting of many individual documents. Each document begins with a exhibit number sticker, much like this one: example. The files are scanned in greyscale....
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24 views

How to segregate resume layouts into different types?

I'm looking for any suggestions on how to segregate resume layout into different types. How do one proceed with such a task? I mean resumes are usually available as pdf or docx format and when we ...
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1answer
65 views

License Plate OCR

Are there any pretrained models or annotated data available for license plate detection? I've seen some sets but most of them are little in size. I'm more interested in prod-like quality. Are there ...
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1answer
564 views

How to create a model to recognize matching label and ROI with OCR

I am trying to make a model in python using Tensorflow to process the Tesseract OCR to detecting and extracting particular ROI from Image. I want to recognize the particular fields and values from ...
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1answer
744 views

Extract text from a image - OCR

This is the first time I am working with OCR. I have an image and want to extract data from the image. My image looks like this: I want to extract the parameters and the values against them. Can ...
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1answer
2k views

How can you build a model that extracts data out from receipts?

I'm trying to build a model that is capable of identifying information on receipts and invoices. I have used google cloud vision api for text extraction from the receipt but the problem is it just ...
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2answers
8k views

how can I solve label shape problem in tensorflow when using one-hot encoding?

I used tensorflow to recognize text from natural images by using convolutional neural network; there is no specific number of characters in the text. To make a successful training I should convert the ...
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32 views

Extracting document templates from similar documents

Using very basic techniques (zone segmentation + OPTICS) I was able to organize a set of around 10^4 business documents (invoices, receipts) into hierarchy of clusters of documents of similar layout. ...
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1answer
4k views

Pretrained handwritten OCR model

I've been looking around for pretrained models dedicated to handwritten OCR. So far I've found very little. Could you please share, if you know any? I find tesseract...
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1answer
187 views

Fake News Detection problem

I would like to work on a project for Fake News Detection especially for Indians news which are in different languages and different formats. Fake news as image with no or very less text Fake news on ...
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41 views

How to build a OCR for reading text from image?

This is my first time working on a OCR application. I have lot of scanned images of English text-book pages like this and I want to build a OCR using DL to ...
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409 views

how to resize image without changing DPI in opencv for detecting text and feeding into OCR?

i resized the image using open cv and it changed the dpi of the image from 300 dpi to 90 dpi . What is the correct way to resize image without changing its dpi in open cv . if we feed the resized ...
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3k views

how to resolve this error in Tesseract : (2, 'Usage: pytesseract [-l lang] input_file') [closed]

pytesseract.pytesseract.tesseract_cmd = r'/usr/local/bin/pytesseract' img = Image.open("/content/drive/My Drive/abc.jpg") print(pytesseract.image_to_string(img)) ...
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10 views

detect diagram region in research papers

How can I detect diagram region and extract it from a research paper
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1answer
106 views

optical chemical structure recognition from images

I want to recognize name of the chemical structure from the image of chemical structure, like in the given image it is benzene structure I want to recognize that it is benzene from the image(I should ...
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1answer
57 views

Evaluating information extraction from structured documents

I'm trying to find metrics to evaluate multiple algorithms for key information extraction from already OCRed invoices. For instance, such an algorithm, given an invoice, could find that: ...
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2answers
2k views

Document Layout Analysis - state-of-the-art?

What is the current state-of-the art within document layout analysis? I.e. detecting columns, separating images from text, distinguishing between page numbering and text and so on. I am looking for ...
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230 views

Image Classification approach for Text images

Let me introduce myself as a beginner to machine learning problems. We are trying to build a system to classify images of text-data like bills, orders, bank-statements etc. We started with the image ...
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1answer
91 views

Classifying Letters using CNN - Help

so some context, I'm trying to develop an OCR (for fun) and for that reason I decided to first find text within a page, parse it in to letters within the text and from there try and classify the ...
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0answers
32 views

Best OCR approach on documents with different formats to find one specific information

Unfortunately, because of confidential data, I can't give a more specific explanation. The Problem So I've got a few documents that in general contain the same information but have different formats....
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1answer
47 views

training neural nets for OCR

we are trying to build an in house OCR system to extract alphanumeric strings from images (kindly note, most of our clients cant afford to send their data onto the cloud so it rules out any API from ...
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1answer
1k views

Reading meters with tensorflow

I'm new to ML world and been reading about ML and TensorFlow. My goal is to read the following example in real time with Android phone: So I tried firebase ML OCR and it works really good, it reads ...