MorpheusID: A journey into verifying users' identity smoothly

 

 MorpheusID

A journey into verifying users' identity smoothly

 

Introduction

MorpheusID is an innovative solution for identity verification that uses a combination of identity card validation and gesture-based detection to verify the authenticity of a user in just 30 seconds. By using a custom-trained model with TensorFlow, MorpheusID is able to track Romanian identity cards and enhance the image quality for more accurate results. The plugin also utilizes Google Vision as an OCR tool to extract the necessary details from the ID, and has a data pipeline in place to process and template each ID pattern. The application is visible at https://morpheus-identity.com/.

 

Caption 1. Short example of current UI integration

 

To further improve the accuracy of the verification process, MorpheusID utilizes mediapipe for gesture-based tracking and employs a Laplassian variation to avoid blurring. The whole flow is delivered in a user-friendly manner through the use of React with Chakra UI.

Journey so far

MorpheusID first began back in August as a project by two individuals at HackTM, the biggest hackathon in Eastern Europe, where it won in the AI, Payments, and Cybersecurity verticals. 

From there, the team behind MorpheusID went on to win Startup Weekend, a local competition focused on the business side of things. They were also selected as finalists in the Innovation Labs, the largest pre-accelerator for startups in Romania.

 

Caption 2. HackTM result back in August 

 

Caption 3.Moment during the InnovationLabs presentation

 

Since then, the team has expanded to seven members and has gone on to win the Rubik Cube accelerator. They have also successfully implemented their solution with two clients.

 

Machine Learning Course Application

For the context of the Machine Learning laboratory, we took the opportunity to focus improving the whole flow with a dedicated precheck mechanism for incoming IDs. Essentially, we needed a firewall to prevent 'bad images' to reach our backend. If this were to be handled completely on the client side, this would mean fewer requests and lower operation costs for our product.

This precheck implied two things: 

- a manual verification of the gestures before sending them to the backend pipeline;

- a way to ensure the quality of the image containing the ID. 

 

 

Unfortunately, there is no clear way of measuring that so we resorted to a more obvious approach. In order to figure out if the MRZ on the ID is visible, we need to initially find the ID and control the blur level by giving the end user dynamic prompts.

Technical details

As mentioned earlier, MorpheusID uses a custom-trained model with TensorFlow to track Romanian identity cards and enhance the image quality for more accurate results. This model is trained specifically to recognize the unique patterns and features of Romanian IDs, ensuring a high level of accuracy in the verification process.

We used a cured dataset of over 200 images containing Romanian Identity Cards collected from a campaign soon after InnovationLabs took place. This enabled us to tweak the algorithm easier for our specific use case and allowed us to give improved directions to the end user in order to obtain the best possible output.

 

Caption 4. Real-time ID tracking using Tensorflow for Romanian IDs

 

The plugin also utilizes Google Vision as an OCR tool to extract the necessary details from the ID, such as the user's name and date of birth. This allows for a quick and efficient way to verify the user's identity without the need for manual data entry, which is one of the main reasons why companies look for thrid parties to handle user verification, as the process in itself is rather time consuming.

MorpheusID has a data pipeline in place to process and template each ID pattern, allowing for easy comparison and verification of the user's identity. The plugin also employs mediapipe for gesture-based tracking and uses a Laplassian variation to avoid blurring, further improving the accuracy of the verification process.

Finally, the whole flow is delivered in a user-friendly manner through the use of React with Chakra UI, ensuring a smooth and seamless experience for the user.

Overall, MorpheusID is a cutting-edge solution for identity verification that uses a combination of identity card validation and gesture-based detection to verify the authenticity of a user in just 30 seconds. With a custom-trained model, OCR technology, a data pipeline, and gesture-based tracking, MorpheusID is able to provide a high level of accuracy and convenience for users.

Research and further developments

In today's digital age, user identity verification is more important than ever. With the increasing prevalence of online fraud and identity theft, it is crucial that businesses and organizations have reliable ways to verify the authenticity of their users. MorpheusID offers a unique solution for identity verification that combines identity card validation with gesture-based detection to provide a fast and accurate way to verify users.

According to a study by Javelin Strategy & Research, identity fraud has cost consumers billions of dollars in the past year alone. In addition, a report by the National Institute of Standards and Technology (NIST) found that user identity verification using internet activity can be an effective way to combat fraud and improve security.

MorpheusID's combination of identity card validation and gesture-based detection provides a reliable and convenient solution for user identity verification. Its custom-trained model, OCR technology, data pipeline, and gesture-based tracking make it a valuable tool for businesses and organizations looking to protect their users and prevent fraudulent activity.

Bibliography

Interesting papers related to ways of preventing malicious users  through other means, such as montioring user activity and using that as a measure of user reliability:

1. "Digital Identity Verification: A Survey of Techniques and Challenges" by F. Abbasi and M. K. Rehman (IEEE Access, 2018): This paper provides an overview of various techniques used to verify digital identities and discusses the challenges involved in this process.
2. "The Digital Footprint: An Overview of Online Identity Management" by S. K. D. J. K. D. D. R. D. W. (International Journal of Information Management, 2016): This paper discusses the concept of digital footprint and the various factors that contribute to it, as well as the implications of online identity management for individuals and organizations.
3. "Online Identity Verification: A Survey" by M. A. Baset, M. A. Imran, and M. Yousaf (IEEE Access, 2019): This paper presents a survey of various approaches to online identity verification, including biometric methods, knowledge-based methods, and possession-based methods.
4. "A Survey of Digital Identity Management: Issues and Challenges" by S. M. A. Hossain and M. M. Rahman (IEEE Access, 2016): This paper provides an overview of digital identity management, including the challenges and issues involved in establishing and maintaining a digital identity.
5. "Internet Footprint: A New Form of Digital Identity" by C. C. S. H. and M. B. (International Journal of Computer Science and Information Security, 2013): This paper discusses the concept of internet footprint as a new form of digital identity and the potential risks and benefits associated with it.

I have posted this blog initially in December 2022, check it out at: https://morpheus-machine-learning.blogspot.com/2022/12/morpheusid-journey-into-verifying-users.html