To truly become a global leader in recognition technology, you need to solve the hardest problems. And that’s precisely what we did. How? By being the first to develop a solution for one of the most complex challenges in pattern recognition—automating the recognition of hand print and cursive writing.
Parascript has been a global leader in all character recognition types (machine print, hand print and cursive) for more than a decade. While other Intelligent Character Recognition (ICR) engines were still deciphering separated characters in print, Parascript scientists were already working relentlessly to develop the first connected handwriting recognition solution—all while continuously improving our techniques in the challenging arena of machine print and hand print. We’re proud to be industry pioneers and continue to set the pace for products that surpass industry benchmarks for read rates and accuracy.
Parascript’s innovative culture is what makes us the trusted provider for a broad range of recognition technology. And it’s what has allowed us to forge ahead with these standout developments which, together, comprise the Parascript Difference.
Unique pattern recognition engine
Our advanced pattern recognition technologies focus on the anatomy of a written word. Much like how humans use context to read words that have been partially scrambled (yuo cna lkiley raed tihs wthiuot a pborlem),the Parascript engine achieves similar recognition through a two-pronged, context-driven approach:
- Character and letter-type identification—The engine identifies the beginning and ending of letters, even when they are connected.
- Word-level analysis—The engine uses known context to prove its assumptions about letter types against complete words, as opposed to a compilation of individual characters. Performed in real time, this contextual analysis reduces the risk of failing an entire word based on the inability to match that single character with confidence.
Parascript technology employs several advanced functions to classify and optimize documents to accurately read a variety of image types. This includes, document structure analysis, region of interest, indicia/logo identification, template-based analysis, and content recognition. Having successfully identified the document, the Parascript engine then has knowledge to apply context to assist with recognition.
Parascript’s technology recognizes that the features of handwriting have a dynamic pattern. Handwriting, when reduced to its most basic element, is essentially motions made by a writing instrument. Certain symbols embody the essence of all handwriting styles, such as the strokes that describe the trajectories. Parascript calls these strokes XR elements – and they are found in all letters. Combined, XR elements form virtually all letter shapes.
Intelligent recognition dynamically uses context – in a process similar to that of humans – to make up for the natural ambiguity of human handwriting. The software applies this context during the recognition process, rather than afterwards, which improves overall accuracy. XR elements and contextual analysis greatly enhance recognition capabilities, often recognizing poor quality text that OCR and ICR engines miss.
Today, it is commonplace for developers to use multiple recognition engines together in order to maximize recognition capabilities and produce better results. This technique is known as voting.
Many companies vote by using a waterfall method, a sequential process by which a series of engines are individually tasked with recognizing content until a satisfactory result is achieved. For example, when engine 1 does not successfully recognize content, engine 2 is called on, and so on, until an engine shows a high confidence rate, at which point the process stops, whether or not subsequent engines have processed the data.
At Parascript, we believe voting should be conducted by consensus — taking into account how every engine interprets data before arriving at a result. Much in the way that multiple people evaluate a situation and come to a final decision, our products leverage multiple engines and a proprietary voting algorithm which considers a multitude of complex variables available and bases a decision on the intimate knowledge each engine provides.
When it comes to high-quality handwriting recognition, Parascript knows It’s not simply how you use context, but when you use it that makes all the difference. By including context as part of the recognition process, our solution builds highly accurate answers which, in turn, lead to substantially higher recognition rates than engines which only validate answers at the end of the process.
Rigorous testing reaches far beyond our technologies. We put our people to the test, too. Engineers in our Moscow office are put through a 30-day trial that not only tests mathematical ability, but overall problem-solving ability within a real-world environment. We know Parascript’s successes could not be possible without a steadfast group of achievers who never stop striving for more. And being a part of that team means you don’t just score higher than average on a test — it means you’ve demonstrated unique problem-solving abilities.
Parascript is dedicated to staying at the forefront of recognition technology by continuously striving to exceed industry expectations. We are especially pleased to have our technology and proven capabilities acknowledged by these prestigious awards:
- SignatureOnline™ voted best performance for online signature verification at the 10th International Conference on Document Analysis and Recognition.
- SignatureXpert® awarded best performance for forensic signature verification at 12th International Conference on Frontiers in Handwriting.
- Parascript was awarded the prestigious STAR Supplier Award by Lockheed Martin (2010) for its performance and contribution to the success of the USPS Remote Computer Reader system.
Learn more about the powerful technology at the core of Parascript’s high-performance solutions.
See how Parascript grew our legacy of innovation and became the global leader we are today.