OCR (optical character recognition) is a technology-based technique for deciphering printed or handwritten text characters contained in digital copies of physical documents, such as scanned paper files. OCR is fundamentally concerned with examining a document's text and converting the characters into machine-readable code for data processing. Occasionally, the term "text recognition" refers to OCR.

Table Reader OCR can extract tables from scanned, standard PDFs or image files and then use OCR technology to recognise PDF characters or pictures in several languages. It supports drawing lines to recognise characters and generate new tables in Windows and Mac OS X. The resulting table can then be saved in various file formats, including CSV, XLS, XLSX, and HTML.

Table Reader OCR

The Table Reader is a simple software tool designed to assist you in analysing n-dimensional tables from a variety of different file types and converting them to CSV, SAV, or OTIS file formats. It can process data from multi-dimensional functional tables, do table lookups, and provide display features.

Numerous industries rely on excel sheets and offline forms for their operations. However, searching among these sheets and forms becomes challenging at some point. Manually populating these tables is time-consuming and increases the likelihood of data entry errors. As a result, table extraction is a more beneficial solution for business use cases such as invoice and form automation.

How Optical Character Recognition works

To convert the scanned image to text, OCR examines the patterns of dark and light that constitute the letters and numerals. Since OCR systems must recognise characters in various typefaces, rules are implemented to assist the system in matching what it sees in the image with the appropriate letters or numbers. While early OCR systems were developed to function with a single, purpose-built font, some newer OCR systems can even recognise handwriting. Intelligent character recognition (ICR) is the name of this technology (ICR).

To ensure the best OCR performance, it is critical to scan the document in its most precise form. Errors can be introduced by blurred text or marks in the copy. While OCR systems read text character by character, the result is instantaneous. You can check for mistakes throughout the process or the conclusion, and some tools include built-in error detection.

To ensure that OCR produces the best possible results, you must scan the document in its original format. Smudged or obscured text or markings on the copy may result in errors. Characters are identified one by one in OCR programs, yet the process is so fast that the results appear instantaneous.

Types of OCR

OCR are classified into the following categories:

Optical word recognition: detects actual words in the typewritten text.

Intelligent character recognition (ICR) uses machine learning to recognise glyphs or characters in handwritten print script or cursive text one at a time.

• Individual words in the printed or cursive text are recognised by intelligent word recognition (IWR). This is especially advantageous for languages that lack distinct glyphs in cursive script.

Functions of Optical Character Recognition

I. Copy-paste document:

The most common and well-known application of the OCR tool is to convert a scanned file and enable users to copy-paste the content as text into a clipboard. Before OCR was accessible, considerable time and money were spent completing or redoing all of this. Naturally, human error was a factor, as retyping introduced several inaccuracies and errors.

II. Scanning of coupon codes:

With the proliferation of mobile apps and mobile-ready programs available today, retailers continue to offer deals that frequently direct customers to this platform. Although printed forms, newspaper coupons, and loyalty stamp cards have become obsolete, this straightforward promotional strategy is still employed in digitalised form.

III. Office filing system:

The OCR tool enables you to bid farewell to paper documents and welcome digital filing. Scanned and converted items can easily be located as machine-readable files that can be searched for any text information within them, including their name, keywords, or phrases.

IV. Automatic data extraction:

In addition to filing, OCR systems aid in eliminating manual encoding and reducing human data entry errors. Large and small businesses alike rely on OCR to automate data entry and, of course, to sort.

V. Text Extraction from Images:

Instantly extract text from photographs and images. Once the image has been translated using the OCR tool, the contents can be copied and searched just like a machine-readable document.

How OCR is helping businesses

I. Increased Productivity:

OCR software enables businesses to increase their productivity by enabling faster data retrieval when necessary. The time and effort formerly needed by staff to extract relevant data can now be redirected to key operations. Additionally, staff no longer need to make multiple trips to the central records room to retrieve essential documents, as they may do so without leaving their desks.

II. Cost Savings:

Using OCR enables businesses to reduce their reliance on professional data extraction services. One of the primary benefits of OCR data entry methods. Additionally, this technology reduces numerous additional costs, such as copying, printing, and shipping. As a result, OCR avoids the expense of misplaced or lost papers and provides further savings through the recovered office space that would have been used to store paper documents.

III. Disaster Recovery:

One of the primary benefits of employing OCR for data entry is disaster recovery. When data is kept electronically on secure servers and distributed systems, it stays secure in an emergency. When a fire breaks out unexpectedly or a natural disaster strikes, the digitized data can be promptly retrieved to ensure operational continuity.

IV. Improved Customer Service:

Numerous inbound contact centers frequently supply information their clients seek. While some call centers offer the necessary information to customers, others will be required to swiftly obtain certain personal or order-related information to complete their requests. Rapid data accessibility becomes critical in these situations. OCR enables the systematic storage and retrieval of documents digitally at lightning speed. This significantly reduces customer wait times, hence improving their experience.

V. High Accuracy:

One of the most significant issues associated with data entry is inaccuracy. Reduced errors and inaccuracies arise from automated data input methods such as OCR data entry, resulting in more efficient data entry. Additionally, OCR data entry can successfully address issues such as data loss. Due to the absence of human intervention, issues such as inadvertently keying in incorrect information can be addressed.