Text Recognition

Extension Description

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

Available in: Block Coding, Python Coding
Mode: Stage Mode
WiFi Required: Yes
Compatible Hardware in Block Coding: evive, Quarky, Arduino Uno, Arduino Mega, Arduino Nano, ESP32, T-Watch, Boffin, micro:bit, TECbits, LEGO EV3, LEGO Boost, LEGO WeDo 2.0, Go DFA, None
Compatible Hardware in Python: Quarky, None
Object Declaration in Python: tr = TextRecognition()
Extension Catergory: Artificial Intelligence

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.

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:

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.
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:
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.

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.