Extract Text from Images: A Step-by-Step Guide to Optical Character Recognition (OCR)

Why OCR is Important

OCR technology has been around for decades, and its importance cannot be overstated. The technology has found its way into various applications, from automating data entry processes to data analysis. By extracting text from images, businesses can automate repetitive tasks, reduce errors, and cut labor costs.

The USPS Flats Sequencing System (FSS) is an enormous OCR system that processes 300,000 pieces of mail daily and sorts them for 125,000 delivery addresses with incredible precision. This system significantly reduces the need for manual sorting and handles large envelopes, magazines, catalogs, and circulars quickly and accurately.

Accessibility is another crucial aspect of OCR technology. For individuals with disabilities, especially those who are visually impaired, accessing information can be challenging. OCR technology plays a vital role in making digital content more accessible, inclusive, and fair. By converting documents into digital text, screen readers can read aloud, making it possible for visually impaired individuals to access information.

How OCR Works

OCR technology involves taking text from sources like scanned documents, receipts, and forms and converting it into a digital, machine-readable format. Once digitized, the data can be easily edited or changed as needed, which is much harder to do with non-digital formats.

The process of OCR involves several steps, including:

• Pre-processing: The image is cleaned up by removing noise, skewing, and adjusting the brightness and contrast.
• Feature extraction: The image is analyzed to identify the features of the text, such as the shape and size of the characters.
• Classification: The extracted features are used to classify the characters, and the text is reconstructed.
• Post-processing: The reconstructed text is reviewed for accuracy and errors are corrected.

Roboflow’s OCR API

Roboflow’s OCR API is a powerful tool that enables developers to extract text from images with ease. The API is powered by DocTR, a machine learning-powered OCR model that is highly accurate and efficient.

To use Roboflow’s OCR API, you need to follow these steps:

Step 1: Set Up Your Roboflow Account

To get started, create a free Roboflow account and log in to access the platform.

Step 2: Install Dependencies

Open a terminal or command prompt and run the following command to install the required libraries:

pip install inference inference-sdk

Step 3: Extract Text From Images

After installing the dependencies, you can initialize the InferenceHTTPClient with the API URL and your API key to load the OCR model. Open a Python file and run the following code:

import os
from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://api.roboflow.com/v1/ocr",
    api_key=os.environ["ROBOFLOW_API_KEY"]
)

result = CLIENT.ocr_image(inference_input="./image.jpeg")

print(result)

Applications of OCR

OCR technology has numerous applications, including:

• Data entry: OCR can automate repetitive data entry tasks, reducing errors and increasing efficiency.
• Data analysis: OCR can help in data analysis by extracting relevant information from images and documents.
• Document management: OCR can help in document management by converting paper-based documents into digital format.
• Artificial intelligence: OCR can be used in artificial intelligence applications, such as image recognition and natural language processing.

Conclusion

Extracting text from images is a crucial process in various industries, and OCR technology has revolutionized the way we extract text from images. Roboflow’s OCR API is a powerful tool that enables developers to extract text from images with ease. By understanding how OCR works and its applications, developers can harness the power of OCR technology to automate tasks, reduce errors, and increase efficiency.