PixLab Blog

In an era where digital identity verification is critical across industries, PixLab's DOCSCAN API stands out by providing an unparalleled ID scanning solution.

With support for over 11,000 types of identification documents from 197+ countries, DOCSCAN unifies ID Scan into a single, seamless REST API endpoint that is unmatched by other eKYC platforms. Let’s dive into the core capabilities of this powerful tool and why it’s a game-changer for developers.

Why DOCSCAN is a Must-Have for Developers

The DOCSCAN API Endpoint is more than just an ID scan API. Designed to be developer-friendly with RESTful API architecture, it simplifies the complex process of identifying, extracting, and validating personal data from IDs, passports, driver's licenses, visas, birth & death certificates and more.

• Single Endpoint Access
  With just one API endpoint, https://api.pixlab.io/docscan, developers can integrate ID scanning capabilities effortlessly into their applications. This endpoint unifies ID scanning, eliminating the need for multiple services or platforms to handle various document types.

• Unmatched Document Coverage
  DOCSCAN supports 11,097+ documents, including both national and international travel documents. Whether structured with Machine Readable Zones (MRZ) or not, the API efficiently processes them. No other eKYC platform on the market today provides this breadth of coverage.

Key Capabilities of DOCSCAN API Endpoints

1. Global ID Support
   DOCSCAN is designed to handle IDs from nearly every country in the world, making it ideal for global businesses. From passports and residence permits to birth certificates, the API ensures that organizations can onboard users regardless of their location.

2. RESTful API Architecture
   The API’s REST architecture ensures easy integration across platforms and programming languages, including Python, Java, PHP, and JavaScript. With a well-documented REST endpoint, developers can quickly set up the solution without extensive learning curves.

3. Intelligent Image Handling
   DOCSCAN integrates intelligent image correction, automatically adjusting for skew, distortion, or layout variations to enhance scanning accuracy. This ensures that even low-quality images yield accurate extraction of data.

4. Built-in Face Detection
   For applications that require additional security, DOCSCAN offers face detection and extraction.

5. Privacy-First Processing
   PixLab processes all data in-memory, ensuring no user data is stored on servers. This privacy-first design aligns with regulatory compliance, including GDPR, making it a trustworthy choice for sensitive applications.

Streamlined Integration with Code Samples

DOCSCAN offers ready-to-use code samples that are accessible here making integration a breeze for developers of all skill levels. Whether you’re working on a financial service, e-commerce, healthcare, or travel platform, the code examples available in multiple languages help you quickly adopt DOCSCAN into your existing project.

Conclusion

PixLab’s DOCSCAN API Endpoint sets a new standard for identity verification, offering a unified, powerful, and developer-friendly platform. With comprehensive global document coverage and advanced features like face detection, it helps businesses scale their eKYC operations effortlessly.

Whether you're building solutions for financial services, healthcare, travel, or e-commerce, the DOCSCAN API endpoint offers scalable, privacy-first, and seamless ID scanning capabilities. Start leveraging DOCSCAN today to simplify identity verification across your digital platforms.

Explore Further:

• PixLab eKYC Platform
• DOCSCAN API Documentation
• PixLab
• FACEIO

Liveness detection is a critical component in biometric security systems, ensuring that the face being scanned is from a live person rather than a photograph, video, or mask. FACEIO, a leader in facial authentication technology, addresses these challenges with its advanced AI models. This blog post explores how FACEIO resolves liveness detection issues, leveraging sophisticated algorithms and security practices.

What is Liveness Detection?

Liveness detection is a security feature used in facial recognition systems to verify that the scanned face is from a live individual. It prevents spoofing attacks by detecting natural facial movements and responses. Various techniques employed in liveness detection include:

• Motion Analysis: Detects natural movements such as blinking and head movements.
• Texture Analysis: Differentiates between the texture of live skin and that of a photograph or screen.
• Challenge-Response: Prompts the user to perform actions like blinking or smiling to prove liveness.

Implementing Liveness Detection with FACEIO

FACEIO provides an easy-to-integrate solution for facial authentication with built-in liveness detection. Here is a step-by-step guide to activate liveness detection on your FACEIO Application:

1. Setting Up FACEIO:

   • Sign up and create an account on the FACEIO Console.

2. Integrating FACEIO SDK:

   • Add the fio.js JavaScript SDK to your project by creating an application first on the FACEIO Console, and follow the integration guide using your favorite JavaScript framework whether it is React, Next, Vue, Svelte or React-Native.

3. Initializing FACEIO:

   • Initialize a new fio.js object instance in your JavaScript code with your Application Public ID as follows: javascript const faceio = new faceIO("your-application-pub-id");

4. Implementing Liveness Detection:

   • Activate Face Anti-Spoofing first by connecting to the FACEIO Console, then Navigate to the SECURITY tab from the manager main view. Once the target application selected. Activate the Protect Against Deep-Fakes & Face Spoof Attempts security option as shown below:

     async function performLivenessCheck() {
      try {
          const response = await faceio.authenticate({ action: "liveness-check" });
          if (response.livenessScore > 0.9) {
              console.log("User authenticated successfully");
          } else {
              console.warn("Liveness check failed");
          }
      } catch (error) {
          console.error("Liveness check failed", error);
      }
     }
     

Advanced Security Features of FACEIO

FACEIO's commitment to security extends beyond basic liveness detection. Here are some of the advanced features that enhance its security:

• Multifactor Authentication (MFA): Combine facial recognition with other authentication methods for added security.
• Customizable User Prompts: Tailor instructions and prompts shown to users during the liveness check.
• Analytics and Reporting: Access detailed reports on authentication attempts to monitor and improve system performance.

Best Practices for Secure Implementation

FACEIO provides several security best practices to ensure robust protection against spoofing and other security threats:

• Reject Weak PIN Codes: Ensure users create strong PIN codes during enrollment.
• Prevent Duplicate Enrollment: Avoid multiple enrollments by the same user.
• Protect Against Deepfakes: Use liveness detection to counteract spoofing attempts.
• Forbid Minors: Prevent minors from enrolling in the application.
• Always Ask for PIN Code: Require PIN code confirmation during authentication for added security.
• Enforce PIN Code Uniqueness: Ensure each user's PIN code is unique.
• Ignore Obscured Faces: Reject partially masked or poorly lit faces.
• Reject Missing HTTP Headers: Prevent requests without proper origin or referer headers.
• Restrict Domain and Country: Limit widget instantiation to specific domains and countries.
• Enable Webhooks: Use webhooks for real-time updates on user interactions.

Conclusion

Integrating FACEIO for liveness detection and facial authentication in JavaScript significantly enhances digital security. Its robust API and user-friendly JavaScript library make it easy for developers to implement biometric authentication, preventing spoofing and unauthorized access. FACEIO's advanced features and best practices ensure both security and user experience are prioritized, making it a valuable addition to any web application's defense against modern threats.

For more information, visit the FACEIO website.

Published in: Level Up Coding

PixLab is thrilled to announce the launch of FACEIO's pioneering Age Verification Widget, a remarkable addition to the FACEIO SDK suite, specifically designed for web and mobile platforms. This state-of-the-art widget provides real-time age verification, ensuring that users can access content suitable for their age group, thereby promoting a safer digital environment.

Key Features and Benefits

• Instant Verification: The FACEIO Widget verifies user age in milliseconds, using advanced facial analysis to swiftly differentiate minors from adults.
• Enhanced Compliance: With precise age distinction, businesses can effortlessly adhere to regional and global age-related regulations, minimizing legal risks.
• Seamless Integration: Developers can easily incorporate the widget into existing platforms with minimal effort, supported by comprehensive documentation available on our Integration Guide and Developer Guides.

A Tool for All Digital Arenas

Whether you're managing an online gaming site, a digital marketplace, or a content streaming service, the Age Verification Widget is your solution to maintaining age integrity online. It ensures that each user's experience is not only compliant with legal standards but also tailored to their age-specific needs.

Future-Proof Your Platform

As digital interactions become increasingly personalized and regulated, integrating robust age verification technology is more crucial than ever. The FACEIO Age Verification Widget is more than just a tool—it's an investment in your platform's future, safeguarding your operations and enhancing user trust.

For more details on how to get started, visit our detailed documentation provided in the Integration Guide and the Developer Guides.

• In today's digital world, face authentication has become an essential part of our daily lives.
• From unlocking our smartphones to accessing secure online accounts, face recognition technology has made our lives more convenient and secure.
• However, with the rise of deep fakes and face spoofing attacks, the need for advanced face anti-spoofing and livesness detection solutions has never been greater.

What is Livesness Detection and Face Anti-Spoofing?

• Livesness detection introduced in late 2023 and already integrated and available to FACEIO customers, also known as face anti-spoofing, is a security feature that ensures that the person being authenticated is a living human being and not a photo, video, or mask.
• This feature is crucial in preventing unauthorized access to sensitive information and systems.
• However, livesness detection can be challenging to implement, as it imposes severe restrictions during authentication.
  • For example, users are not allowed to have a smartphone, laptop, or LCD screen behind them during the authentication process.
  • If any of these devices are detected, the authentication process is aborted, and an PAD_ATTACK error code is raised instead.

Example of Spoof ATTACKS deterred by our ML new model

PixLab's New Single Shot Liveness, Face Anti-Spoof & Deep-Fake Detector Model To the Rescue

• PixLab, a leading provider of AI-powered face authentication & Age Verification solutions, has recently released a new single shot livesness, face anti-spoofing, and deep-fake detector model for FACEIO.
• This innovative model is designed to provide enhanced security and accuracy in face authentication, making it an essential tool for businesses and individuals alike.
  • One of the key features of this model is its ability to detect faces in a single shot, without requiring multiple images or video frames.
  • This makes the authentication process faster and more convenient for users, while still maintaining a high level of security.
  • In addition, this model is highly accurate and can detect even the most sophisticated face spoofing attacks, including those that use 3D masks and other advanced techniques.
  • This makes it an ideal solution for businesses and organizations that require a high level of security and accuracy in their face authentication systems. Customers are already invited to try out the new face Anti-Spoofing model directly within the FACEIO Widget!

Conclusion

• PixLab's new single shot livesness, face anti-spoofing, and deep-fake detector model is a game-changer in the world of face authentication.
• With its advanced AI algorithms and highly accurate detection capabilities, this model provides enhanced security and convenience for users, while still maintaining a high level of accuracy and reliability.
• As the use of face recognition technology continues to grow, it is essential to have advanced solutions like PixLab's new model to ensure the security and privacy of our personal information.
• Whether you are a business owner or an individual user, this model is an essential tool for anyone who values security and convenience in their face authentication systems.

PixLab is thrilled to announce the release of PixLab Annotate 1.97, the latest version of our cutting-edge online image annotation tool. Designed to streamline and enhance the process of image labeling and segmentation, PixLab Annotate 1.97 is packed with new features and improvements that make it an indispensable tool for machine learning and computer vision projects.

Key Features of PixLab Annotate 1.97

• Enhanced Labeling Tools: The new version includes advanced rectangle and polygon zoom drag labeling tools, making the process of annotating images more precise and efficient.

• Optimized for Instance Segmentation: PixLab Annotate 1.97 is optimized for instance segmentation tasks, including support for Mask R-CNN, ensuring compatibility with advanced machine learning models.

• Client-Side Persistent Storage: With the introduction of client-side persistent storage, your data remains on your device, eliminating the need for data transfer and enhancing security and speed.

• Full-Screen Display and Snapshot Capture: The full-screen mode and snapshot capture feature allow for a more immersive and detailed annotation experience.

• Consistent JSON Output: The tool generates consistent JSON output, which is readily accepted by most machine learning frameworks, facilitating seamless integration into your workflow.

• Improved Label Management: Create, modify, and delete labels with ease, thanks to the improved label management system.

• Annotation Events Tracking: Keep track of your annotation history with the enhanced tracking feature, which includes undo and redo options for better control over your work.

• User-Friendly Interface: The interface of PixLab Annotate 1.97 is intuitive and easy to navigate, making it accessible for both beginners and experienced users.

Why Choose PixLab Annotate 1.97?

PixLab Annotate 1.97 is more than just an annotation tool; it's a comprehensive solution designed to meet the needs of professionals in the field of machine learning and computer vision. Whether you're working on a small project or a large-scale enterprise task, PixLab Annotate 1.97 offers the reliability, efficiency, and accuracy you need.

Get Started Today!

Experience the power and convenience of PixLab Annotate 1.97 today. Visit PixLab Annotate to explore these new features and see how they can transform your image annotation tasks. Join the community of professionals who are already leveraging the benefits of PixLab Annotate in their projects.

• Project Home Page: pixlab.io/annotate
• Annotate Online Web Application: annotate.pixlab.io

Stay tuned for more updates and enhancements as we continue to evolve and improve PixLab Annotate to meet your needs.

Happy annotating!

Kuala Lumpur, Malaysia - In a significant industry recognition, PixLab's Document Scanner has been awarded the title of the top KYC ID Verification provider for MyKAD in Malaysia. This honor underscores the company's commitment to excellence and its continuous drive to provide the best identity verification solutions in the market.

PixLab's Document Scanner has set itself apart with its cutting-edge machine learning technology, user-friendly interface, and stringent data security measures. Businesses across Malaysia have lauded the product for its accuracy and efficiency, making it the go-to solution for KYC ID verification.

Why PixLab Stands Out

PixLab's Document Scanner has been recognized as the number one KYC ID Verification provider for MyKAD in Malaysia. This accolade is not just a testament to the product's superior technology but also its commitment to ensuring a seamless user experience.

• Advanced Technology: Leveraging state-of-the-art machine learning algorithms, PixLab offers unparalleled accuracy in scanning and verifying MyKAD documents. This ensures that businesses can trust the authenticity of the ID being presented, reducing the risk of fraud.
• User-Centric Design: Understanding the importance of a smooth user journey, PixLab has designed its scanner to be intuitive. This means quicker onboarding for customers and less friction in the verification process.
• Data Security: In today's world, data breaches are a growing concern. PixLab prioritizes user data security, ensuring that all scanned information is encrypted and stored securely.

Related Articles

To learn more about PixLab's DOCSCAN API endpoint and its comprehensive features, please refer to the following articles & code samples:

1. Passports, Travel Documents & ID Cards Scan API Endpoint Available.
2. Full Scan Support for Malaysia and Singapore ID Cards.
3. Scanning Malaysian ID Cards with PixLab API.
4. Memindai Kad Pengenalan Malaysia dengan API PixLab: Panduan Lengkap.

Code Samples

• Scan Malaysia ID Card (MyKAD) (PHP Code)
• Scan government issued ID card from Malaysia (MyKAD, MyKID), extract the user face and parse all fields (Python Code)
• Scan an international issued Passport document using the PixLab API. Extract the user's face and display all MRZ fields (PHP Code)
• Scan an international issued Passport document using the PixLab API. Extract the user's face and display all MRZ fields (Python Code)

Press Release

"We are immensely proud of this recognition," said Mrad Chams, CTO of PixLab. "It reaffirms our dedication to providing the best solutions to our users. We understand the critical role identity verification plays in today's digital landscape, and PixLab strive to offer a product that is both reliable and easy to use".

As PixLab continues to innovate, the industry and its users can expect even more advanced features and enhanced user experience in the future. With its eyes set on global expansion, PixLab is on a trajectory to redefine identity verification standards worldwide.

For more information about PixLab and its award-winning Document Scanner, please visit PixLab's website.

PixLab, a leading provider of Machine Vision is thrilled to unveil our latest creation: Tiny Dream. This header only, C++ library represents a significant leap forward in the realm of Stable Diffusion Inference, all neatly packaged into a C++ framework.

What is Tiny Dream 🔥

Tiny Dream is a header only, dependency free, partially uncensored, Stable Diffusion implementation written in C++ with primary focus on CPU efficiency, and smaller memory footprint. Tiny Dream runs reasonably fast on the average consumer hardware, require only 1.7 ~ 5.5 GB of RAM to execute, does not enforce Nvidia GPUs presence, and is designed to be embedded on larger codebases (host programs) with an easy to use C++ API. The possibilities are literally endless, or at least extend to the boundaries of Stable Diffusion's latent manifold.

Features 🔥

For the extensive list of features, please refer to the official documentation here.

• OpenCV Dependency Free: Only stb_image_write.h from the excellent stb single-header, public domain C library is required for saving images to disk.
• Smallest, Run-Time Memory Footprint for Running Stable Diffusion in Inference.
• Straightforward to Integrate on Existing Codebases: Just drop tinydream.hpp and stb_image_write.h on your source tree with the Pre-trained Models & Assets.
• Reasonably fast on Intel/AMD CPUs (Benchmarks): With TBB threading and SSE/AVX vectorization.
• Support Real-ESRGAN, A Super Resolution Network Upscaler.
• Full Support for Words Priority: Instruct the model to pay attention, and give higher priority to word (keywords) surrounded by parenthesis ().
• Support for Output Metadata: Link meta information to your output images such as copyright notice, comments, or any other meta data you would like to see linked to your image.
• Support for Stable Diffusion Extra Parameters: Adjust Seed resizing & Guidance Scale.

Documentation & Resources to Get Started 🔥

• Getting Started Guide
• C++ API Reference Guide
• Pre-Trained Models & Assets Downloads
• Licensing Tiny-Dream
• Future Project Roadmap

Dive Deeper with GitHub

For those eager to explore the intricacies of Tiny Dream, we've made the entire project available on GitHub. Dive into the code, explore its features, and join our community of contributors. Check out the project here: Tiny Dream on GitHub.

Related Projects 🔥

You may find useful the following production-ready projects developed & maintained by PixLab | Symisc Systems:

• SOD - An Embedded, Dependency-Free, Computer Vision C/C++ Library.
• FACEIO - Cross Browser, Passwordless Facial Authentication Framework.
• PixLab Annotate - Online Image Annotation, Labeling & Segmentation Tool.
• ASCII Art - Real-Time ASCII Art Rendering C Library.
• UnQLite - An Embedded, Transactional Key/Value Database Engine.

In Conclusion:

The release of Tiny Dream marks a pivotal moment for us. We believe in pushing the boundaries of what's possible, and with Tiny Dream, we're one step closer to redefining the future of Stable Diffusion inference. We invite you to join us on this exciting journey, explore Tiny Dream, and witness the future of C++ libraries.

Thank you for your continued support and enthusiasm. Here's to many more innovations ahead!

Stay tuned for more updates and announcements. Your feedback and contributions are always welcome!