OCR software allows you to convert a scanned image into an editable format like word or excel. This article introduces the basics of OCR software, available features and options. We’d show how to navigate through Docsumo’s interface, generate editable files from image files, and save the results. With so many powerful OCR applications available, choosing the right one for you can be confusing.
Use this guide as your first step, offering a brief explanation of the basic capabilities of each product covered.
So, let’s jump right into it:-
OCR (Optical Character Recognition) software is a revolutionary way to extract text from images. By using OCR, you can automate many time-consuming and manual data entry tasks and gain access to previously difficult-to-reach sources of information.
Nowadays, advanced programs like Docsumo have solved this problem by using machine learning to make the process of scanning and correcting documents much more accessible. Using OCR can make your life much easier and help increase productivity in the workplace for various reasons.
Let's take a closer look at the process:
OCR software is a program that can read text from images, scanned documents, PDF files, or live feeds. The goal is to make the data more readily available for storage and manipulation in your computer system. In most cases, this requires further processing before it can be used for anything meaningful (for example, you can scan a document but then need to extract certain words or numbers from the resulting file).
OCR automates scanning capabilities allowing it to scan paper documents, turn them into an electronic format, and then store them in an electronic document management system (EDMS).
The business world has seen a radical transformation in how it operates in the last two decades. The advent of the Internet and its pervasive use have led to tech innovations that have changed the face of business. OCR software is one such innovation that has made a massive difference in how we work.
The OCR workflow consists of several steps executed in series and preparing the image for recognition. OCR software uses advanced algorithms to read and analyze the document, identify text lines and characters, and convert them into machine-encoded text. This machine-encoded text can then be used as searchable content.
The base of this process is the scan or photograph of the document. When scanning, all pages must be examined in one step, making it easier to correct errors in the following process steps:-
The first step is to capture the image. This is usually done with an OCR software scanner but can also be done with a digital camera. The image is then stored as a bitmap or raster image. Each pixel contains color and brightness information for that point on the page in this format. Bitmap files come in many formats, such as TIFF, JPEG, and PNG. The format used will depend on the application intended for use with the OCR software.
The next step is to apply a set of image processing algorithms to improve the quality of the image before recognition. The step includes pre-processing the image file (or scanned page) by applying noise reduction, de-skewing, binarization, and other techniques, depending on the quality of the original image and the software's capabilities.
These algorithms include:-
Binarization -This process converts the entire image into monochrome black and white (grayscale). For example, a halftone photograph may have different shades of gray. In this case, binarization converts various shades of gray into absolute black or white pixels. This simplifies later processing by breaking down the image into just two colors.
Noise Reduction - It is done to get rid of pixels carrying out false information that could affect the extraction.
De-skewing - To rotate a scanned image to get rid of any skewing.
Once the image has been pre-processed, an automated document analysis step tries to detect the type of document being processed. This helps determine how the rest of the OCR process proceeds. For example, if a scanned image is identified as an invoice or purchase order, certain assumptions can be made about what type of data to expect from that document and how it ought to be structured.
This is where the OCR software analyzes and identifies the type of content in the document. It does this by looking for sections of text that are similar to each other to form what's called a "cluster of characters" or "glyph cluster".
Once a template is created based on the whole document, individual fields can be extracted. This is done by segmenting the document into smaller sections containing specific information types (like an address or a phone number). This step may also include keyword recognition. This is done by examining gaps between words or lines of text and making an educated guess based on what it knows about the standard letter.
In this step, OCR software separates each data field (e.g., name, address, etc.) on a document into different zones to be handled separately by extraction tools in the next step.
These algorithms can analyze how many times a particular pixel pattern occurs in an image. The more frequently this pattern appears, the higher chance that it is part of a word. Some OCR software even has pre-trained models to detect specific symbols like digits or punctuation marks.
This step involves extracting all relevant data from each segmented area and putting it into a usable format for your business. Extracted data can be exported to other databases or applications for further processing.
The engine extracts the document's information like headers, footers, and page numbers. It also determines the structure of columns and tables.
Once the images are segmented into lines, words, and characters, they're ready for recognition. During this stage, data is extracted into usable information by comparing the segments against an OCR engine or machine learning model that's been trained on thousands of examples.
OCR software extracts data from each zone with built-in machine learning models or custom models depending on your organization's specific needs.
Now that all of your data has been extracted and stored, you can use it for further use. However, before using it, you must recheck any mistakes in the extracted data. If there are mistakes, you can correct them before using them for your work.
While most OCR engines do an excellent job on their own, some will have you manually look over each document's output before submitting it for processing. Even if the OCR software is highly accurate, there will still be errors that require human validation. This step ensures that the final results are error-free.
Different industries have different requirements, and additional requirements call for various software. To make this choice more manageable, we have compiled a list of things you need to consider when looking for the best OCR software for your business.
The scalability of the OCR software is one of the most critical aspects when choosing an OCR solution. The OCR software should grow with your business so that you don't have to invest in new software every time your business expands.
Data extraction using OCR is not always 100% accurate as some words may be misread while converting them, leading to errors in your document. The best way to deal with this problem is by using an OCR solution that has a high accuracy rate.
An OCR software should integrate well with business processes as it helps in automating a range of tasks. The software should have the ability to be interconnected with third-party applications and incorporated into the existing business processes. This eliminates the need to do manual data entry, thereby reducing the cost of operations.
The OCR software should be integrated with other business-specific applications such as document management systems, accounting software, CRM, and others to streamline their processes and improve efficiency.
Businesses need to leverage analytics and adequately use the data for growth in this digital age. So, choose a tool that can analyze unstructured data and provide you with actionable insights based on it. Any analytics tool must provide meaningful visualizations so you can understand your data at a glance and make better decisions. Make sure the software you choose offers a centralized dashboard where you can view visualizations of all your data in one place.
An OCR software may not work with all types of documents and may require customization according to your needs. So, make sure that the solution provider offers customizable solutions as per the outlined requirements.
In this section, we discuss the parameters you should specifically be looking at depending on your industry while choosing an OCR solution:-
Look for a solution that offers top-notch accuracy and the ability to handle high volumes of documents. Also, find out whether the software provider provides a way to automate the entire process so that you can dedicate your internal staff's time to more strategic initiatives.
You need a robust image capture and document management platform that enables you to capture, store, index, and retrieve all types of documents. One of the essential factors in choosing an OCR software is that it can work with your existing document management system and integrate with other systems your company uses.
You'll want a solution that can handle large-volume digitization of paper records and automate many of the processes involved in retrieving patient files and keeping them up to date. The solution needs to integrate well with the existing workflow processes. It also needs to have a high success rate of extracting patient data for insurance claims processing.
Choosing an OCR software with automated data extraction capabilities will save your business time and money by eliminating the need for manual data entry of receipts or invoices and automatically populating them into your back-end system(s). The more intelligent the recognition, the better suited for retail applications.
Solution that offers a reasonable turnaround time for document processing so that the supply chain is not halted due to slow processing times. A cloud-based solution can help achieve this by scaling up or down depending on your workloads without investing in additional hardware infrastructure.
If the majority of documents you want to scan are property-related, then look for an OCR solution that has features specific to property management such as auto-generating lease abstracts from scanned documents, identifying critical dates in leases such as renewal dates, tracking rent increases and other such features.
Form processing software uses technologies like OCR (Optical Character Recognition) and NLP (Natural Language Processing) to automatically extract and process data from forms.
So how can you leverage Docsumo's form processing software to automate form processing? Here are the five steps:
The first step is to upload all the documents you want to process. You can do this by simply dragging and dropping them onto your dashboard. Alternatively, you can also connect your cloud storage so that Docsumo can directly access all your documents.
Our OCR technology is trained to understand all forms, including handwritten and typed texts, checkboxes, signatures, and more. This means that our form processing software can automatically detect form fields like names, addresses, phone numbers, dates, and more without any human intervention after the initial setup. You can also manually edit detected fields if required.
Once you have approved the suggested field values and annotated them manually if necessary, you can validate them before exporting the data to an external source. Validation rules ensure that all the fields have acceptable input values so they can be processed automatically according to your business requirements in an error-free manner.
Review and approve suggestions made by our algorithm or manually edit if required. Our OCR software also provides you with a review dashboard to search, sort, filter, and download all processed documents based on their status (reviewed/unreviewed). You can also set up notifications to receive an email when team members have processed and reviewed all documents.
Our software automatically creates a .CSV File when you complete the automated suggestions in your pipeline. The .CSV File contains all the corrected text and any annotations and additional text captured during the OCR Review Process.
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
Optical Character Recognition (OCR) is the technology to convert an image of text into machine-readable text. It is the underlying technology for various data extraction solutions including Intelligent Document Processing. However, OCR is not smart enough to figure out the context in a document - it works simply by distinguishing text pixels from the background and finding a pattern. This limitation could cause inaccuracy in captured data that could directly impact the output of your data extraction model.
Accounts payable is a key financial function for any business. Corporations can have thousands of suppliers; even for relatively smaller businesses, the number of suppliers could be in hundreds. All the invoices they receive from these suppliers come in multiple formats, layouts, and templates - some semi-structured, some unstructured. Therefore, firms expend time and resources to capture invoice information through manual data entry and verification of accounts payable. Manual data entry is not feasible in the long run, definitely not on a large scale. Before we talk about how intelligent invoicing solves the problems associated with manual invoicing, let’s discuss the challenges in much detail.
As most of an organization's information is available in an unstructured format, processing it requires an automated system that can handle documents with minimum human interaction. OCR is one such technology, but its scope is limited as it requires human interaction and is highly dependent on the layout and structure of the document to be processed.These limitations are overcome by Intelligent Data Extraction.Using artificial intelligence, the Intelligent Data Extraction technology extracts data from documents and transforms it into useful information through the extraction process. It functions as a singular tool for extracting information from any type of document and aids in optimizing company operations.