Menu OCR for Efficient On-site Data Capturing
Improve your market research efficiency using AI-powered OCR technology. Embrace rapid and accurate menu data extraction today.
Transform Your Data Capturing with Menu OCR
Scan and process menu cards with Klippa’s AI-powered OCR software. Process a larger volumes of menus faster while reducing operational costs.
Streamline Data Capture for Menus with Ease
Automate Menu Card Data Extraction in 3 Simple Steps
With our OCR software, you can automatically extract data from restaurant menus to ramp up your market research. Integrate our menu card OCR software via API or SDK.
Uploading documents to the API
The first step is providing a picture or a PDF file of a menu card to our API. Usually this is done from a mobile app, email, FTP or web application.
Image to text using menu OCR
As soon as a picture or PDF of a menu card has been received, each page is converted to a TXT file. In this step all the text from the document is extracted, but it is not yet structured.
Getting JSON output from the API
The Klippa Parser takes the TXT gained from the OCR in step 2 and converts it into structured JSON using machine learning. The JSON is then returned as output from the API. The menu card data is now extracted.
From here the separate fields of the menu can easily be processed into your database. Specifications for differentiating data on a menu can be set beforehand.
The image on the left is a simplified example of the JSON response.
Which Data Fields Can Be Extracted with OCR for Menu Cards?
Below are the examples of data fields that can be extracted. The number of fields is fully customizable. Need additional menu fields? Just ask!
Enjoy the Benefits of Menu Data Extraction with OCR
Reduce Cost
Spend less on manual data extraction with Klippa’s menu OCR.
Improve Speed
Process menus automatically in seconds and optimize your output.
Boost Productivity
Spend less time on manual data extraction for menus.
Minimize Errors
Prevent data entry errors with high quality data extraction on menus.
We Take Your Data Privacy & Security Seriously
“It is extremely pleasant to work together with a party that is as ambitious as we are. The willingness and speed with which Klippa implemented specific modifications for us is impressive.”
Let’s begin!
Discover the power of Klippa’s advanced OCR technology, as our experts help you to revolutionize menu scanning today.
Frequently Asked Questions
How much does menu card OCR cost?What menu card formats are supported?How does menu card scanning work?What industries currently use Klippa’s OCR software?What languages does Klippa support?Can Klippa convert menu cards to CSV, XLSX, XML or JSON?How can I integrate Klippa’s menu card OCR software?What machine learning techniques are used for menu card image recognition and OCR?
How much does menu card OCR cost?
The pricing structure for Klippa’s menu card OCR depends on the amount of fields and the document volume to be processed.
Get in touch with our product specialists for a quote.
What menu card formats are supported by Klippa?
There are different formats between countries with regard to composition and contents of menu cards. In general, we support all formats, layouts and contents. These can be classified, organized and made searchable.
In case you wonder if we support a certain menu card or have any other question, feel free to contact us for more information.
How does Klippa’s menu card scanning work?
You can use our OCR SDK scanner for direct scanning or upload photos and PDFs to our OCR API, starting the process with a simple action and then letting technology take over.
Klippa’s software then analyses the light and dark patterns that make up the letters and numbers to convert the scanned image into text. After that, data fields are identified and extracted from the menu cards.
To learn more about the process, click on the link to our blog about menu card scanning.
What industries currently use Klippa’s OCR software?
Klippa supports a wide range of clients in a variety of industries. Our engine extracts data from menus using OCR and machine learning technologies.
Menu card extraction is most commonly used by clients who aim to offer food delivery services, informative services for local restaurants, quick allergy information, or any other service related to menus.
What languages does Klippa support?
Currently, Klippa supports all Latin languages. Our engine performs best on price tags in English, Dutch, Norwegian, Danish, Swedish, Finnish, Italian, Portuguese, Spanish, German, and French.
However, other languages can be supported on request. We’re open to training our machine learning models. If you have a specific case, don’t hesitate to contact us.
Can Klippa convert menu cards to CSV, XLSX, XML or JSON?
Yes we can. We take pictures, PDF’s/ equivalents, and convert them to readable text using OCR. From there we use machine learning to turn the text into structured data. Although we mostly use JSON for this, depending on your preferences we can also convert documents to CSV, XLSX or XML.
How can I integrate Klippa’s price tag scanning OCR software?
Our API can be implemented into any software, web or mobile solution that you may be using. The main source of communication is JSON, so it is independent of specific programming languages.
Our mobile SDKs have been built using native IOS (Swift) and native Android (Kotlin). This means they can be implemented into native apps, but they can also be wrapped for cross-platform languages such as Xamarin, ReactNative, Nativescript, Flutter, PhoneGap, Cordova, Ionic and more.
Klippa’s solution is made in a developer-friendly way. Our software is well-documented, so that developers can have all the information they need to successfully implement OCR API.
What machine learning techniques are used for menu card image recognition and OCR?
Klippa uses a combination of multiple techniques to extract data from menu. The first step is a deep learning algorithm to detect bounding boxes which comes from the field of computer vision. Klippa leverages this technique to identify and crop menus from images from for example supermarket shelves. As soon as this is done we perform OCR to identify what text is written on the cropped images.
When we have identified all text, we use natural language processing (NLP) to determine which text has what meaning. By looking at words and characters we automatically determine what text belongs to the description, what numbers to the prices, volume and serial number for example.
In the end, our backend processes this information into a JSON output that is easy to process for our clients.