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How optical character recognition raises the stakes for online gambling

New use cases for Optical Character Recognition (OCR) technology continues to materialize. Veterans of the OCR and document capture industry that we speak with are gobsmacked when we share how this well-established technology is being used in new and innovative ways. A recent example involves the use of computer vision in the online gaming industry.

The global online gambling market is currently valued at around $45 billion and estimated to double to more than $90 billion within the next 5 years.

Online gambling consists of playing casino games, poker and sports betting via the internet. Due to increased adoption, widespread internet connectivity and mobile technology advancements such as smartphones and tablets, the online gambling market is currently experiencing astounding growth.

These technical and network enhancements also give rise to new types of online gambling such as “live dealer” casinos. Online gambling recreates the look and feel of a brick-and-mortar casino and features genuine professionally trained croupiers managing classic casino table games such as blackjack, roulette and poker. The croupier is responsible for collecting stakes and paying out winnings and uses high-quality live HD streaming to do so. One of the latest ways online casinos can transmit this real-time card data from the virtual tables to the players is through the use of OCR technology.

A brief history on OCR

Optical Character Recognition (OCR) is the electronic translation of scanned images of machine-printed text into machine-encoded text. It’s used to convert books and documents into electronic files or to publish text on a website. OCR makes it possible to edit the text, search for a word or phrase, store it more compactly, and display or print a copy. Based on the analysis of sequential lines and curves, OCR makes “best guesses” at characters using database look-up tables to closely associate or match the strings of characters that form words.

The basis of OCR technology was originally patented out of Germany in the 1920s, but it was not until 1950 that David H Shepard, a former cryptanalyst from US military, delivered the world’s first commercial OCR system. In the 1960s, Reader’s Digest built an OCR document reader to digitize serial numbers from coupons returned from print advertisements. By 1974, Ray Kurzweil developed the first omni-font OCR system – a computer program capable of recognizing text in any standard font, initially designed as a reading machine for the visually impaired. With Kurzweil’s application, the computer ingests printed content and it reads the text aloud to its audience. The technology went mainstream and was sold to Xerox in 1980 who further commercialized paper to text conversion.

Changing the game for virtual croupiers

So how is the technology being used in online gambling? Optical character recogntion effectively monitors the gaming room using specialized cameras to capture the raw game data and analyse the cards, suits and symbols. Next, it’s cross referenced to a rapid response quick lookup database which then displays the results on the screen. This real-time data allows players to make more informed betting decisions.

Traditionally online gambling games were managed by use of radio frequency identification (RFID); each card within an active deck equipped with a tiny microchip scanned by the dealer, before being dealt on the table. The adoption of OCR has rendered this approach obsolete, and dealers can now use conventional playing cards rather than expensive RFID-enabled alternatives. This results in better user experience, with players no longer noticing the difference between playing online or in a real casino, as relevant information such as value of a hand, stakes, etc. are displayed in real time. This approach also benefits the croupiers as they are better able to monitor the games they are managing and can analyse the player’s bets and hands in real time.

OCR technology is still the backbone of the document scanning and document management industry but has also been incorporated into several other applications such as invoice processing systems, data entry automation, automatic number plate recognition, passport recognition and ID verification and business card capture. The technology is also finding new markets such as robotic process automation (RPA), eDiscovery and data loss prevention (DLP) as well as still being a mainstay of the assistive technology market for blind and visually impaired users. With the rise of new use cases for computer vision in the Internet of Things (IoT) field, we’re excited to see what the next 12 months holds.

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