The global OCR market is expected to reach $13 billion in the coming five years, mainly driven by an increase in the adoption of OCR software and cloud-based services. It was valued at approximately 38 billion in 2024, and it is significant across verticals. Past the process of reading from the images, OCR technology is now applied for data extracting from PDF files, scanned images, and even paper documents. Data entry for digital archiving has become easier and more flexible as a result of the newer models of neural networks and artificial intelligence.
In this article, we will explore how OCR helps to extract text from various sources and why it is an essential asset to any company or person.
Let’s get started.
How Image OCR Automates the Data Extraction from PDFs and Images?
Image OCR is used as a sophisticated method of automation in processes of data acquisition, thus eliminating the risks of error and time loss. But the question that might be lingering in most people’s minds is, ‘How does it work?’ Okay, let’s analyze it step by step.
1. Image Segmentation
Image preprocessing (segmentation) is the first process in OCR technology, the first of which is image segmentation. In this process, the scanned image is divided into many regions so that the text can be separated from other related components, such as images or borders. The OCR system recognizes these areas and processes them in such a way that it can concentrate on the text areas only. By breaking it down into segments, it means that OCR tools can analyze the content much better and hence have a higher level of accuracy when it comes to data extraction.
2. Neural Network Analysis
Subsequently, as concerns the segmented text regions, the OCR system uses neural networks for the analysis. These networks are trained on large data bases involving a range of fonts, languages, and handwriting styles. Neural networks reconstruct the human brain’s functioning and start learning the patterns and features in the text. This stage seems paramount in the process in order for the OCR system to read the text correctly, whether it is formatted or written in a different style.
3. Character Recognition
The text can be passed through the neural network, after which the next stage is character recognition. Here, the OCR system detects individual characters from the segmented regions, which are obtained as the first step. There are more sophisticated versions of the OCR tools that employ AI to enhance character recognition and enable identification even where the characters are distorted or in less known fonts. This is the most crucial zone of the OCR technology; this is where the act of’reading” the text takes place.
4. Word Representation
It’s typically thought of as comprising two stages: First, individual characters are recognized, and then these are pieced together into words by the OCR system. This word representation step therefore entails assessing and judging the identified characters with the aim of deriving words from them. The system employs dictionaries and language models to allow only those words that will make sense in the context. This step prevents some problems that may appear due to the wrong recognition of characters, which happens in texts that contain illegible fonts and styles.
5. Post-Processing
Post-processing is an essential phase where the OCR system refines its output. It checks for errors, corrects misrecognized text, and ensures that the final output is as accurate as possible. This stage often involves comparing the recognized text against a known database of words and correcting any inconsistencies. Post-processing enhances the reliability of the extracted data, making it more usable for further processing or analysis.
6. Text Extraction
The last stage of the OCR process is the extraction of text. Thus, after all the aforementioned steps, the OCR system takes the recognized text from the image or PDF. It may also be employed for a range of uses, for instance, data entry, document processing, or other AI techniques. But other than that, this automation of text extraction also reduces time consumption and lessens the possibility of error during transcription compared to the manual method.
Best OCR Tools for Data Extraction from Images & PDFs
When it comes to choosing an OCR tool, there are several options available, each offering unique features. Here are some of the best tools to consider:
1. Picturetotext.info
Picturetotext.info is a powerful OCR tool that excels at converting images into text. This tool offers a user-friendly interface as well as high accuracy in text recognition.
Besides, it supports multiple languages it can handle complex documents with ease. So, if you’re dealing with scanned documents, handwritten notes, or printed text, Picturetotext.info is what you need as it provides reliable and fast text extraction.
2. Ifimageediting.com
Another great OCR tool tested by me is Ifimageediting.com, a web platform that provides professional image editing services as well as fully automated text extraction. Ideally, this tool serves users who wish to extract text from an image that might as well need some sort of resizing, erasing, or color change. Indeed, with all the foregoing features fully incorporated, Ifimageediting.com guarantees that the extracted text is not only correct but is formatted to the highest quality available.
3. Ocr2edit.com
Ocr2edit.com is an all-round OCR tool that can extract texts from images as well as from PDFs. That’s why it has an intuitive and rather minimalistic interface that allows users to upload their files and get the text output in the shortest time possible. It is most effective when the user wants to convert a number of documents to be processed into editable text, which is very helpful for businesses that are involved in large amounts of data processing.
Conclusion
Image OCR tools are used to extract data from other formats, particularly PDFs and images, so that important information does not end up in formats that cannot be easily read. They increase accuracy and precision and minimize manual activities and time consumption. Picturetotext.info is a marvelous OCR tool that can help businesses attend to strategic concerns. It is better to select a tool that would address your particular needs and work with simple documents, images, or any other format to store and further utilize the received data.
