Computer Vision, Explained: What Computer Vision Means for Automated Document Processing
Computer vision helps computers to “see” — using an approach that aims to replicate human vision. Although it might sound sci-fi at first, computer vision is a natural development of artificial intelligence (AI) and deep learning that is quickly becoming the norm across industries.
With the help of computer vision, we can identify objects and visual patterns much faster than the human eye can. Computer vision also helps to reduce employee burnout by preventing employees from engaging in rote, repetitive tasks.
Computer vision plays a key role in modern document processing techniques, by identifying patterns and “reading” without the help of manual templates. Let’s take a look at how computer vision works — and what it means for the future of document processing.
What is computer vision?
Computer vision is “an artificial analogue of human vision in which information about the environment is received by one or more video cameras and processed by [a] computer: used in navigation by robots, in the control of automated production lines, etc.”
In other words, computer vision uses images detected by a camera to perform functions that would otherwise require human guidance. By feeding a computer thousands of labeled images, deep neural networks can develop algorithms that can identify patterns in new, unlabeled images.
Over time, computer vision can even identify patterns faster and more accurately than a human could. For its widespread potential use cases, computer vision has recently become a booming industry.
The idea behind computer vision is to be an “artificial analogue of human vision” — not to reproduce human vision precisely. While we don’t have an algorithm that can simulate the human mind, there are plenty of ways in which computer vision is able to recognize patterns in the way humans do. Systems with computer vision gather visual data, which is applied to an algorithm that is constantly using feedback to become more accurate.
How computer vision works in modern intelligent document processing (IDP)
As computer vision becomes more efficient, it has been introduced into a number of fields:
- Sorting items on the assembly line
- Avoiding vehicular collisions
- Classifying web images
- Quality management
- Plant disease detection
There are hundreds of use cases for computer vision. Now, computer vision is being used in intelligent document processing (IDP) to make document processing more powerful and capable than ever before.
When machine learning is used in document processing, algorithms grow more accurate as more data is processed. Over time, deep learning (multi-layered machine learning) teaches the computer to differentiate between different images, and to make educated predictions when there is uncertainty.
Pattern recognition is possible with the help of convolutional neural networks, which can break down images into pixel-sized patterns. Convolutional neural networks can identify larger shapes, then use machine learning algorithms to make more specific predictions as they process more complex detail.
The benefits of using computer vision in modern IDP solutions
Before IDP, document processing used a process called optical character recognition (OCR) — a computer-based application that has been in place since the 1980s. Traditional OCR relies on preset templates to gather data from documents, which aims to avoid manual processing.
However, traditional OCR only works with structured documents, with identical formatting. The slightest change in format — in invoices, for example — will require an entirely new OCR template.
With computer vision, IDP eliminates the need for templates altogether. Because computer vision is able to identify data based on predictive algorithms, there is no need for manual intervention. IDP can use computer vision to process semi-structured and even unstructured documents with deep learning that improves over time.
In fact, Rossum’s IDP can quickly exceed both the accuracy and efficiency of human document processing — with up to 98% accuracy in the first month. But computer vision doesn’t mean your employees are being replaced by machines.
Instead, your employees can go from painstaking manual processing to supervising a streamlined IDP program. By using IDP to process documents, businesses can avoid burnout, frustration, and human error.
Harnessing computer vision with Rossum
Computer vision is central to Rossum’s approach to IDP. You can train Rossum to read documents without configuring a single template — adapting to formatting changes along the way. With human supervision, each correction is quickly incorporated into Rossum’s ever-improving predictive model.
To see computer vision in action, try our 14-day free trial. With integration across plenty of common platforms, Rossum is easy for you to deploy, and easy for your employees to supervise.
Plus, Rossum protects the security of your documents with security measures that are audit-compliant across many industries. Try out intelligent document processing with Rossum, and learn how your business can harness the power of computer vision.