Text Recognition

Extension Description
AI to analyze images from text recognition – handwritten and printed.

Introduction

What is OCR?

OCR stands for Optical Character Recognition. It is a widespread technology used to recognize text inside images, such as scanned documents and photos.

OCR technology converts virtually any image containing written text (typed, handwritten, or printed) into machine-readable text data.

News Reporting

OCR Technology became popular in the early 1990s while attempting to digitize historical newspapers. Since then, technology has undergone several improvements. Nowadays, solutions deliver near-to-perfect OCR accuracy.

Applications of OCR

Following are a few applications of OCR in different industries:

  1. Converting Historic Books or Book Images into PDF: OCR is widely used to convert historical books into editable documents like PDFs. The structured nature of printed copies makes it much easier to analyze them.Books OCR
  2. Security (License Plates): Another everyday use case of OCR is license plate recognition. This requires detecting the license plate and then recognizing its characters. The plate’s shape is relatively constant, so people use simple reshaping methods before recognizing the digits. Here are some examples from the web:License Plate Detection
  3. Postage: ORC is also widely used in detecting critical information from post letters like Pincode, addresses, etc. Usually, the post letters are designed to make it easy for the computer to get the relevant information from a particular part of the image.

Python Functions

This function helps turn the video on/off on the stage with a defined level of transparency.
Syntax: video(video_state = “on”, transparency = 1)
This function is used to analyze the image received as input from the camera, for the handwritten and printed text.
Syntax: analysecamera()
This function is used to analyze the image received as input from the stage, for the handwritten and printed text.
Syntax: analysestage()
This function is used to analyze the image received as input from the current backdrop, for the handwritten and printed text.
Syntax: analysebackdrop()
This function is used to analyze the image received as input from the current costume of the sprite, for the handwritten and printed text.
Syntax: analysecostume()
This function is used to analyze the image received as input from the image URL specified, for the handwritten and printed text.
Syntax: analyseURL(url = “https://ai.thestempedia.com/wp-content/uploads/2022/07/Hello-World.png”)
The function reports the handwritten text identified from the analysis.
Syntax: handwrittentextresult()
The function reports the printed text identified from the analysis.
Syntax: printedtextresult()
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PictoBlox Blocks

turn () video on stage with () % transparency block controls the control the camera feed on the stage.
This block is used to analyze the image received as input from the camera, for the handwritten and printed text.
This block is used to analyze the image received as input from the stage, the current backdrop, and the current costume, for the handwritten and printed text.
This block is used to analyze the image received as input from the image URL specified, for the handwritten and printed text.
Once you have analyzed the image for printed text, you can use a printed text result block to get the recognized text from the image in a string format.
Once you have analyzed the images for handwritten text, you can use a handwritten text result block to get the recognized text from the image in a string format.
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