This article deconstructs intelligent image data extraction and explores the benefits for every professional taking the plunge into the realms of AI. The cherry on top is the intuitive step-by-step platform created by Alphamoon to guide users to get the best out of image data extraction. Regardless of the industry, if you aim to optimize the workflow, improve the life-work balance for yourself and your staff, and create space for innovation, then this is for you.
Data Extraction Deconstructed
When it comes to any type of data extraction, categorization, and interpretation, manual processes have long been surpassed. Nowadays, using automation is the norm. This is mainly due to the ever-increasing data volumes and, if anything, keeping one’s sanity. Still, jokes aside, our human eye can only do so much when dealing with so many informational layers.
Let’s first look at how we migrate and use data extraction.
Data extraction is the process by which businesses obtain data from databases or SaaS platforms and duplicate it to a data warehouse for use in reporting, analytics, or machine learning. We traditionally categorize data extraction based on its design and structure: logical vs physical data extraction.
Let’s give examples and skip any technical buzzwords:
Logical Data extraction: exporting a table in CVS.
Flat files such as CVS are usually simple text that does not require any metadata.
Did you know that Microsoft Excel accounts for 90 percent of flat file databases?
Physical Data extraction: transferring data such as photographs, biometrics, and more complex file formats from one device to another.
In a physical extraction, the contents of a device’s memory are copied bit by bit.
By the way – did you know that although faster and quicker, logical extraction produces less information? Physical extraction is more time-consuming and complex, but gives more insights.
Want to learn more? Check out this data extraction tools comparison.
What is image data extraction?
Businesses and employees have used image data extraction for many years. So far, only pre-outlined reading skills have been used to extract their visual data. Image data extraction uses feature extraction and heavily relies on metadata.
In image processing, feature extraction transforms raw data into numerical data for better conservation of the data and improving the machine learning results. This data includes visible data like colors, shadows, and shapes and backend data such as the mean and the grayscale pixel value.
Thanks to machine learning and auto-identification text, intelligent picture data extraction is the new, cutting-edge technique to grow your company units.
You can’t begin explaining intelligent image data extraction without first addressing Computer Vision & OCR, the Body & Soul of any image data extraction platform.
Although the current iteration of computer vision appears to be a recent development, it is the result of decades of research. Midway through the 1960s, MIT released “Project MAC,” an acronym for Project on Mathematics and Computation. It goes back to the XIXth century, starting with Herman Hollerith’s tabulator sorter and culminating with the punch machine.
One of the most recent developments of Hollerith’s discovery is computer vision, a branch of artificial intelligence that teaches computers how to see 2D and 3D pictures and objects.
Deep learning-based computer vision is skilled at swiftly and precisely classifying and processing large amounts of visual input and formulating conclusions or suggestions based on the data.
In a nutshell, it teaches the computer to process an image on a granular lever for an accurate prediction of the object. In Image Data Extraction, we think of Computer Vision as the Body.
Imagine you wanted to digitize a printed contract, a letter, an invoice, or a handwritten note. You would end up typing and retyping, correcting errors for hours on end.
Alternatively, you may use an optical character recognition program and a scanner (or a digital camera) to convert all the necessary materials into digital format in a matter of minutes. OCR, or optical character recognition, operates through vectors. This aforementioned feature extraction classifies and reports back to the data bank, where it compares with existing feature vectors stored in the bank.
We look at OCR as the Soul of image data extraction and processing.
Although the precise methods by which humans can recognize objects are not yet fully understood, scientists are already aware of the three fundamental principles of integrity, purposefulness, and adaptability (IPA).
These ideas form the basis of Alphamoon’s IDP platform, which includes the AI OCR feature – among other components that are used like building blocks to solve complex document workflows.
AI OCR enables the platform to mimic real-world or human-like recognition. More so, while conventional OCR software is constructed using a rule-based model, Alphamoon’s model uses intelligent document processing.
Curious what intelligent document processing is?
IDP refers to a process of transforming unstructured data extracted from documents into structured and relevant information. We covered the topic in our extensive guide to intelligent document processing.
Back to image-to-data processing. We’ve established the difference between AI OCR and conventional OCR.
Why is this light years ahead of other platforms?
In a nutshell, by using IDP, the platform combines machine learning, artificial intelligence (AI), and natural language processing (NLP) to provide highly accurate data extraction and classify the extracted information.
Classification is the keyword here, and thanks to its accuracy, the data can be further streamlined and successfully used regardless of the industry and language you’re operating in. Character recognition is so sensitive that it can pinpoint even handwritten calligraphy on a microscopic level.
With IDP, your processes level up in a snap.
Interested in learning more about the IDP platform by Alphamoon?
What about the final readable format?
If the tabulator was operating on paper, contemporary AI can recognize and process various formats. Users may extract data from several files, including PDF forms, TIFF, BMP, TXT, DOC, DOCX, XLS, XLSX, EML, and more.
Fun fact, this is all possible thanks to this 27-year-old lad named EXIF, a format for storing metadata in images.
EXIF (Exchangeable image file format) is a standard that outlines the picture, sound, and supplemental tag formats that digital cameras (including smartphones), scanners, and other devices handling image and sound files captured by digital cameras will accept.
Now that you know the body & soul of image data extraction, let’s explore how you can use it.
Let that sink in.
Examples of industries & big names using it
What are some industries that heavily rely on Image Data Extraction?
|Industry||Use of image data extraction|
|Banking||Digital paper checks, processing contracts, invoices, etc.|
|Healthcare||CT, MRI, Radiology, ultrasound scanning, etc.|
|Manufacturing||Barcode reading, QA inspection, packaging inspection, etc.|
|Travel||Airport self-check-in machines, facial recognition during security, etc.|
What are some of the big fish worldwide using Image Data Extraction & what do they use?
|Softeq||Computer vision – object tracking and recognition capable of face, gesture, movement recognition, and background separation.|
|IBM Watson||AI – fast processing medical images and efficient data interpretation with information from various databases.|
|Enlitic||Deep learning – enables radiologists to read cases 21% faster.|
|Tesla||Computer Vision – The software behind Tesla’s self-driving cars.|
|Alphamoon||AI + OCR – error-free legal documentation, invoice, and skip tracing automation.|
How can image data extraction improve your company’s operations?
Let’s take a closer look at how implementing something as basic as image data extraction can and will instantly increase your performance and revenue. If you’re part of the mainstream industries such as medical or banking, you’re most likely already using a vast array of data extraction and sorting tools.
Chances are that today only, there is probably not one soul working in banking that hasn’t opened an excel spreadsheet.
If you’re more of a niche or only now finding your footing, these following features might help you decide on opting for an OCR platform such as Alphamoon for setting your affairs in order, with no need for hiring any extra staff.
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Why should you use an image data extraction tool like Alphamoon
Alphamoon quickly extracts visual data and metadata from a vast array of formats and exports in high quality.
- Helps you save time
- Helps you minimize errors
- Cuts your costs on both resources & payroll
It’s easily integrable with a vast array of software you use in your daily operations.
- Reduces the software clutter
- Saves money on extra training for yourself and your staff
- It’s measurable & acts as a to-go source of truth
Enhanced results guaranteed from the first use.
- OCR is sensitive to handwritten papers
- Operates in 10 languages (for now
- Highlights and allows you to edit all fields
A tireless algorithm that keeps on learning.
- Easily recognizes the type of document
- Learns how to recognize acronyms in your texts
- It’s a private source that caters to your extraction and processing needs
Read about the most common challenges of image-to-text extraction here.
See it in action with Alphamoon
Did you know that one of the biggest roadblocks to implementing new systems is training yourself and your staff to use them? What if we tell you we have a solution that is so intuitive that not only requires minimal to no training, but will enable creativity and excellency in 3,2,1…
Alphamoon’s OCR is taught thanks to the usage of machine learning; it processes thousands of documents and gains expertise by learning from image data extraction.
As mentioned in feature number #4, the secret really lies in continuous learning. Every batch of documents you upload and process improve future results. This further translates into good ROI in the long term for once, which pretty much means you’re getting back substantially more than what you’re deciding to invest now.
If you like the sound of that, you should hear our numbers.