Optical Character Recognition (OCR) technology enables machines to recognize text in images, handwritten or typed text, and convert them into machine-readable characters. OCR solutions find extensive use in various fields such as data entry automation, form recognition, indexing documents for search engines, and automating various tasks in the banking and healthcare sectors. Recognizing features of OCR technology is essential for understanding its practical applications and working principles, which is a vital part of AI-900 Microsoft Azure AI Fundamentals exam. Herein, we cover key features of OCR technology.
1. Text Recognition:
The very basic feature of an OCR system is recognizing text from images or a handwritten document. For example, you can take a photo of a page in a book, and an OCR will be able to transform the text in that image into machine-readable text. This feature is essential for any task involving a digital transcription of text from paper-based records.
2. Image to Text Conversion:
This is an advanced feature where the OCR system recognizes not just typed text but can also transcribe text seen in an image. For instance, signs in a street captured within a photo can be transcribed into editable text.
3. Language Support:
Modern OCR systems feature support for various languages. Advanced OCR systems support hundreds of languages, including those that do not follow a Roman script.
4. Scalability:
OCR systems can efficiently process large volumes of data. This feature is essential in a generation where data influx is high and manual entry is no longer a feasible solution.
5. Font Recognition:
An advanced feature in OCR systems is the ability to recognize different types of fonts and styles. The more font types the OCR can identify, the more flexible it is at transcribing different types of birth certificates, bank statements, driving licenses, passports, and application forms.
6. Handwriting Recognition:
Select OCR solutions also have handwriting recognition capability. They are trained on enormous data sets of handwriting variations, enabling them to recognize and interpret handwritten text.
Azure Computer Vision API
Microsoft Azure’s Cognitive Services includes Computer Vision, which offers OCR capabilities. Azure OCR supports several languages and can also recognize handwriting. To use Azure’s OCR, follow these steps:
- The first step involves converting the image file into a byte array.
- Next, create an instance of ComputerVisionClient.
- Call the RecognizePrintedTextInStreamAsync or RecognizeTextInStreamAsync method on your client in order to recognize printed or handwritten text, respectively.
- Review and process the resultant data as per your application needs.
Here’s a simple piece of example code:
byte[] imageBytes = GetImageAsByteArray(imageFilePath); //This is a user-defined function to convert an image to byte array
ComputerVisionClient client = new ComputerVisionClient(new ApiKeyServiceClientCredentials(subscriptionKey))
{
Endpoint = endpoint
};
using (Stream imageStream = new MemoryStream(imageBytes))
{
OcrResult ocrResult = await client.RecognizePrintedTextInStreamAsync(true, imageStream, OcrLanguages.Unk);
//true is to detect orientation
//processing the ocrResult is user-specific and dependent on the needs of your application
}
In conclusion, OCR technology is an indispensable element of AI and its applications are numerous. With OCR, key tasks can be automated, saving businesses and other entities a whole lot of time and resources.
To ensure a thorough understanding of the OCR solutions, the above-listed features will be crucial. Knowing these features will help you in your AI-900 Microsoft Azure AI Fundamentals test, preparing you well for questions related to OCR technology. Added to this, knowledge about Microsoft Azure’s Cognitive Services, specifically the Computer Vision API will be advantageous for the exam.
Practice Test
True or False: Optical character recognition can transform paper documents into searchable and editable data.
- True
- False
Answer: True
Explanation: Optical character recognition is a technology used to convert scanned paper documents, PDF files or images captured by a digital camera into editable and searchable data.
Optical character recognition technology cannot be used for reading barcodes and QR codes.
- True
- False
Answer: False
Explanation: In addition to text, OCR technology is also capable of interpreting barcodes and QR codes.
In Microsoft Azure, which AI service is capable of recognizing printed and handwritten text?
- A. Azure Cognitive Services
- B. Azure Machine Learning
- C. Azure Information Protection
- D. Azure Data Factory
Answer: A. Azure Cognitive Services
Explanation: Azure Cognitive Services includes the Computer Vision API that supports Optical Character Recognition (OCR) capabilities.
True or False: Using Optical character recognition, one cannot convert non-searchable documents like images into searchable ones.
- True
- False
Answer: False
Explanation: One of the primary uses of OCR is to convert non-searchable documents like PDFs or scanned images into searchable formats.
Which of these features can be provided by Microsoft Azure’s OCR solutions?
- A. Extract printed and handwritten text
- B. Recognize layouts and structures
- C. Extract text in multiple languages
- D. All of the above
Answer: D. All of the above
Explanation: Microsoft Azure’s OCR solutions are capable of text extraction (both printed and handwritten), recognizing layouts and structures of the documents and text in multiple languages.
True or False: Optical character recognition can only read text from documents in the English language.
- True
- False
Answer: False
Explanation: OCR is capable of reading text from documents in multiple languages, not just English.
OCR technology can be used to:
- A. Automate data entry processes
- B. Automate invoice processing
- C. Automate form processing
- D. All of the above
Answer: D. All of the above
Explanation: OCR technology used in Microsoft Azure can automate various processes like data entry, invoice handling, form processing etc.
True or False: OCR can be used in license plate detection and recognition.
- True
- False
Answer: True
Explanation: OCR technology can be used in various ways including license plate recognition, which is a form of image-based sequence recognition.
Which API from Azure Cognitive Services can read text from images?
- A. Vision API
- B. Text Analytics API
- C. Speech API
- D. Search API
Answer: A. Vision API
Explanation: The Vision API from Azure Cognitive Services has the ability to recognize text from images.
Optical character recognition cannot be used for processing:
- A. Invoices
- B. Checks
- C. Contracts
- D. None of the above
Answer: D. None of the above
Explanation: OCR can be used for automated processing of various types of documents including invoices, checks and contracts.
True or False: Optical character recognition systems can only work with printed text.
- True
- False
Answer: False
Explanation: OCR systems can work with both printed and handwritten text.
Interview Questions
What is Optical Character Recognition(OCR)?
OCR is a technology used to convert different types of documents, such as scanned paper documents, PDF files or images captured by a digital camera, into editable and searchable data.
What is an OCR solution related to Azure AI?
Azure AI provides the Read API in Azure Cognitive Service for OCR, which extracts printed and handwritten text from images and documents with preserving their layout.
Does the OCR service in Azure AI supports multiple languages?
Yes, Azure’s OCR service can extract text or recognize characters from over 60 languages.
How does Azure AI OCR determine the language in the image?
Azure AI OCR uses machine learning algorithms to automatically detect and recognize the language in the image or document.
What are the input formats supported by Azure’s OCR solution?
Azure’s OCR can take image file as input. It supports formats like JPEG, PNG, BMP, PDF and TIFF.
What type of information can OCR solutions extract from documents or images?
OCR can extract printed and handwritten text from documents or images. It can also retain the formatting features like layout, color, and font styling.
Does Azure AI OCR support handwritten text?
Yes, Azure’s OCR service can handle printed text as well as handwritten text.
Can OCR recognize text from any type of image?
While OCR is a powerful tool, its ability to recognize text can be impacted by the quality of the image, the clarity of handwriting in the case of handwritten text, and other factors such as background noise and lighting.
What kind of applications can you develop using Azure AI OCR?
Azure AI OCR allows developers to build applications that require text extraction from images or documents. This could include applications like an automated data entry system, or a system to digitize printed documents.
Is Azure OCR service limited to specific sectors?
No, Azure OCR is not limited to any specific sectors. It can be used in any field or sector that needs to digitize or transcribe printed or handwritten text.
How can you use the OCR API provided by Azure AI?
The OCR API can be used by sending an HTTP POST request to the Azure OCR service endpoint, with the image or document data in the request body.
What is the Read API in Azure OCR solution?
The Read API is an interface provided by Azure’s OCR service for extracting printed and handwritten text from images and documents. It processes the document in different stages and provides the result which preserves the layout and formatting of the original document.
In the context of Azure OCR’s functionality, what is bounding box?
The bounding box refers to the coordinates provided in the output by the OCR which specifies the location of the recognized character or word within the image.
Does the Azure OCR service support both synchronous and asynchronous operations?
Yes, Azure AI provides support for both synchronous and asynchronous operations. APIs for OCR like the Read API, work better for large documents and support asynchronous operations.
What does Azure use to improve OCR accuracy over time?
Azure uses machine learning technologies to improve its OCR accuracy over time. It can learn from the diverse set of data provided by its users.
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