The FACEIO development team is pleased to announce the immediate availability of our Liveness Detection, Presentation Attacks Mitigation (PAD) & Face Anti-Spoofing Security Option. A highly requested feature by our customers that is now deployed & fully operational on FACEIO thanks to a PixLab implementation.

Liveness detection in biometrics is the ability for a system to detect if the target face is real from a live person present at the point of capture or fake from a spoof artifact or lifeless body part.

Face Anti-Spoofing on the other side, is the task of preventing false facial authentication when implementing fio.js, our facial recognition library on your web site or application using a smartphone picture, or printed image for an authorized person's face.

Face Anti-Spoofing Security Option

With this security option enabled, Smartphone & Print Attacks originating from a static image or video stream are easily deterred during Authentication & Enrollment when enabled for your FACEIO application.

The Face Anti-Spoofing Security Option is immediately available to trigger from the Application Manager (Security Tab) on the FACEIO Console.

Press Release & Model Roadmap

Our Press Release document including a general overview of the approach used to implement Face Anti-Spoofing for FACEIO is available to consult at: cdn.faceio.net/faceio_liveness_detection.pdf.

This implementation & further model enhancements, are pushed transparently, and no action or code changes are required on your side. Just an option to trigger from the Application Manager on the FACEIO CONSOLE.

Implementation Overview

Once a new user enroll or authenticate on your application, the Face Anti-Spoof engine shall be triggered to filter out spoof & presentation attacks. Upon an attack is detected, the fioErrCode.PAD_ATTACK error code is raised, and you should act accordingly such as banning the acting user depending on your policy.

Please note that Face Anti-Spoofing mitigation is a resource intensive operation, therefore it is available starting from the Business Plan, and up. Nevertheless, it takes less than 600 milliseconds to execute thanks to a heavily optimized implementation.

We are pleased to announce the graduation of the FACEIO's NPPM Package from beta to general availability, so it's even easier to leverage the power of facial authentication to your Node based web application.

The fio.js NPM package supports Web developers using FACEIO by reducing friction when implementing fio.js, our facial recognition library on their web sites or apps regardless of the underlying JavaScript framework whether it is React, Angular, Vue, Next, React Native or even Vanilla JavaScript.

Getting Started

To help you get started using FACEIO' NPM Package, we've outlined some basic steps below. For more information, refer to the official integration guide:

• NPM Package Home: www.npmjs.com/package/@faceio/fiojs
• Github Repository: github.com/symisc/faceio-npm

Community Tutorials

The following, high-content, community contributed guides & tutorials should help you implement fio.js on your web application using your favorite JavaScript framework:

• Implement a Facial Recognition Authentication Using React.js and TailwindCSS
• Implementing Web based Facial Authentication with FACEIO's NPM Package
• FACEIO's fio.js V1.9 Released with Face Duplication Prevention
• Authentication is hard. Let FACEIO handle it for you
• Using React-Typescript With FaceIO for User Face Authentication
• Log in/Sign up form using FaceIO, Next.js and Tailwind CSS
• How to use Facial Recognition to Enhance user Experience on your Website using FaceIO
• How to Authenticate a User with Face Recognition in React.js
• How to Authenticate a User via Face Recognition in Your Web Application

Share Your Feedback

Finally, if you’ve had a chance to use the new FACEIO' NPM Package, and have any feedback or suggestions you’d like to share, please do reach out to us on the GitHub repository or open a new support ticket via the FACEIO Console. We really look forward to hear back from you!

If you encounter any bugs or technical issues while using our new NPM Package, we want to know so we can make things right. Please be sure to file a report on our GitHub repository.

Starting with the major release of fio.js 1.9, FACEIO Webhooks have been rebuilt from the ground up to improve latency and provide new functionality like payload field inclusion which is available starting from the Business Plan, and up.

Webhooks allows you to receive data and get notified at real-time about the ongoing events during the interaction of the FACEIO Widget with your users (eg. New user enrollment or authentication) in-order to keep your application backend up-to-date & synchronized. FACEIO uses Webhooks to let your system know when such events happen. Events includes New User Enrollment, Facial Authentication Success, Facial ID Deletion, and many other events.

When an event occurs, FACEIO makes an HTTP POST request to the URL you configured for the Webhook. FACEIO’s request includes details of the ongoing event such as the Unique Facial ID of the user being enrolled or authenticated, its gender & age in case of new enrollment, timestamps, event type, IP information, linked payload, and many others details.

Enabling Webhooks

Registering your Webhook endpoint URL for receiving events for your FACEIO application is straightforward as shown in the detailed steps below:

1. Connect to your account via the FACEIO Console first.
2. From the console main view, visit the Application Manager.
3. Select the target application for which you want to setup webhooks for.
4. Navigate to the WEBHOOKS tab from the manager main view.
5. Once the target application selected. Enter your Webhook Endpoint URL for receiving events and save your modification.
6. You're all set. Upon an event is triggered, FACEIO shall make an HTTP POST request to the URL you configured for the Webhook with the appropriate fields.

Major Enhancements

Starting with the 1.9 release, here are the quick highlights, with more details in the Webhooks page dedicated documentation:

• Faster notifications.
• JSON Based POST Requests.
• IPv6 Support.
• Payload Field Inclusion.
• HTTP1.1/2 Protocol Support.
• Full Support for TLS 1.3 Requests.

The PixLab development team is pleased to announce the immediate availability of FACEIO's fio.js V 1.9. A major release which implements highly requested features from our customers including but not limited to:

• Face Duplication (same user enrolling twice or more) Prevention.
• Dynamic Session Reloading without Page Refreshing.
• Faster facial features collection during enrollment.
• Upto 1.3x faster facial authentication operation.
• French, Japanese, Vietnamese & Dutch new language packs.

As usual, this update is transparent to our end users & fio.js implementers, and no action is required on your side if you link directly the library from the FACEIO CDN.

Face Duplication Prevention:

When enabled, this option shall prevent the same user from enrolling twice or more on your application. That is, if the facial features of the user being enrolled are already recorded, the enroll operation is aborted, and the fioErrCode.FACE_DUPLICATION error code is raised to your host application instead. This option is immediately available to trigger from the FACEIO Console. Please refer to the updated boilerplate code to see this feature in action.

When this option is disabled (default case), it is considered, a no-error operation for the same user to enroll twice or more on your application. This will trigger a collision, and ask the user to confirm his PIN code whenever an authentication operation occurs with the user in question.

Session Reloading without Page Refreshing:

The introduced restartSession() method let you purge the current user session and request a new one. By default, sessions in FACEIO starts following the first call to the enroll() or authenticate() method whichever comes first, and are immutable. After successful call to this method, the old session is discarded, a new one is created, and you can perform another round of calls to enroll() or authenticate() for the same user without reloading (refreshing) the entire HTML page or relying on an external JavaScript function such as location.reload() to do so.

Please note that dynamic session generation via this method are available to the Premium Plans only. Think of upgrading your Freemium application from the FACEIO Console first before calling this method on your frontend

Finally, for additional information & to learn more about implementing FACEIO on your website or web application, please refer to the following documents:

• Getting Started Tutorial: Learn the fundamentals about implementing facial authentication on a typical web application.
• Integration Guide: Learn how to implement fio.js, our facial recognition library on your website.
• Developer Center: Code samples, documentation, support channels, and all the resources yo need to implement FACEIO on your website.
• Frequently Asked Questions: Get instant answers to the most common questions.
• Trust Center: Learn how we handle your data securely and in compliance with privacy and legal requirements.

We are pleased to share our Press Release launch document, as well as, new enhancement introduced to FaceIO, our Web based facial Recognition framework for Websites & Web applications with a set of new languages pack for a more than friendly user experience (UX).

Since its launch two months ago, FaceIO have been proven to be a rock solid product, with a slick & easy integration regardless of the underlying JavaScript framework whether it is React.js, Next.js, Vue.js, Angular or even Vanilla JavaScript. As of this announcement, Over 10K FaceIO Applications has been deployed, easing users authentication thanks to a passwordless experience powered by face recognition.

Available Language Pack

• English (en Default, fallback language)
• German (de)
• Portuguese (pt)
• Spanish (es)
• Dutch (nl)
• Japanese (ja)
• French (fr)
• Vietnamese (vi)
• Indonesian (id)
• Malay (ms)
• Turkish (tr)

Upcoming Language Pack

• Korean (kr)
• Arabic (ar)
• Italian (it)
• Simplified Chinese (cz)
• Polish (pl)
• Russian (ru)
• Czech (cs)

FaceIO Launch Press Release

• Biometric Update: PixLab launches face biometrics authentication framework for web applications.
• Symisc Systems Press Announcement: https://cdn.faceio.net/fio-press-release.pdf.

Community Articles & Tutorials

It’s super quick to implement FaceIO, and get it up & running on your website or web application. The following tutorials, and guides should help you roll facial recognition to your web users in a straightforward manner:

• Getting Started Tutorial: Learn the fundamentals about implementing facial authentication on a typical web application. Your first steps with FaceIO...
• Integration Guide: Learn how to implement fio.js, our facial recognition library on your website before rolling facial authentication to your audience...
• Developer Center: Code samples, documentation, support channels, and all the resources yo need to implement FaceIO on your website.
• Frequently Asked Questions: Get instant answers to the most common questions.
• Trust Center: Learn how we handle your data securely and in compliance with privacy and legal requirements.
• Implement Facial Authentication on your Vue.js App.
• How to Authenticate a User with Face Recognition in React.js.
• Face Log in/Sign up form using FaceIO, Next.js and Tailwind CSS.
• How to Authenticate a User via Face Recognition in Your Web Application.
• How to use Facial Recognition to Enhance user Experience on your Website using FaceIO.
• Using React-Typescript With FaceIO for User Face Authentication.

PixLab is delighted to announce the immediate availability of FACEIO, our web-based, facial authentication framework developed from scratch here at PixLab in the past few years.

The TLDR;

FACEIO is a cross-browser, facial authentication framework that can be implemented on any website via simple JavaScript snippet to easily authenticate users via Face Recognition instead of the traditional login/password pair or OTP code.

You can start implementing FACEIO on your website or web-based application immediately by following our getting started guide here.

The Developer Intro

FACEIO is a cross-browser, Cloud & On-Premise deployable, facial authentication framework, with a client-side JavaScript library (fio.js) that integrates seamlessly with any website or web application desiring to offer secure facial recognition experience to their users.

Put it simply, FACEIO is the easiest way to add passwordless authentication to web based applications. Simply implement fio.js on your website, and you will be able to instantly authenticate your existing users, and enroll new ones via Face Recognition using their computer Webcam or smartphone frontal camera on their favorite browser.

Once fio.js implemented on your website, you'll be able to instantly recognize your existing users, on-board new members securely with maximum convenience, and at real-time thanks to passwordless experience powered by face recognition.

FACEIO works with regular Webcams or smartphones frontal camera on all modern browsers, does not require biometric sensors to be available on the client side, and works seemingly with all websites and web-based applications regardless of the underlying front-end JavaScript framework or server-side language or technology.

Features

• Authenticates and confirms identity of users instantly without FIDO keys, OTP codes, or security questions.
• Full cross-browser compatibility (Chrome, Firefox, Safari, Edge & Chromium derivatives).
• Zero external dependency. Only standard technology implemented in plain JavaScript & CSS.
• Defense grade accuracy with less than 100 milliseconds recognition speed powered by state-of-the-art facial recognition engines.
• Highest security standards. Privacy by design with maximum user convenience. No requirements for biometric sensor.

Adding FACEIO to your website

Implementing FACEIO on your website or webapp is straightforward. Before so, you need to create a new application first on the FACEIO Console, and link this resource to your website or web application. The checklist below highlights the steps to follow for a smooth integration of fio.js on your site:

1. Create a new FACEIO application first: Follow the Application Wizard on the FACEIO Console to create your first application and link it to your website or web application.
2. The Application Wizard should automate the creation process for you. Usually, this involve inputting an application name, selecting a facial recognition engine, cloud storage region, reviewing security options, customizing the Widget layout, and so forth...
3. Once your first FACEIO application created, simply implement fio.js, our facial recognition JavaScript library on your website, and initialize the library with your application Public ID.
4. Congratulations 👏. You have FACEIO up & running! Now, it's time to enroll() and authenticate() your first user via face recognition. Refer to the HTML Integration Boilerplate on how to do so...

Some Links to Get Started

It’s super quick to implement FACEIO, and get it up & running on your website or web application. The following tutorials, and guides should help you get started with FACEIO:

• Getting Started Tutorial: Learn the fundamentals. Your first steps with FACEIO...
• Integration Guide: Learn how to implement fio.js, our facial recognition library on your website before rolling facial authentication to your audience...
• Developer Center: Code samples, documentation, support channels, and all the resources you need to implement FACEIO on your website...
• Frequently Asked Questions: Get instant answers to the most common questions.
• Trust Center: Learn how we handle your data securely and in compliance with privacy and legal requirements.
• Implement Facial Authentication on your Vue.js App: In this article we’ll walk through how to set up a vue typescript webpack that uses FACEIO as an authenticator.

Symisc Systems is pleased to announce the immediate availability of PixLab On-Premises for the general public.

PixLab On-Premises allows organizations with restrictive IT policies or requirements for tighter integration to deploy portion or the entire PixLab stack on their own infrastructure, giving them complete control over their media assets. The on-premise version of PixLab contains exactly the same features as the cloud solution, and it will require minimal IT intervention to deploy and maintain.

Notable Features Of PixLab On-Premises

• Complete control over your media assets. No assets leaves the deployment server.
• Passports & ID Cards scanning capabilities similar to the DOCSCAN API endpoint.
• Not Safe for Work (NSFW) content moderation similar to the cloud NSFW API endpoint.
• Image & Video tagging similar to the cloud TAGIMG API endpoint.
• Straightforward & Automated Installation.
• Continuous Updates, Bugs & Security Fixes.
• TLS Encrypted Transaction.
• Completely Removed Telemetry.

Eligibility, Package Order & Delivery

PixLab On-Premises is designed to address critical privacy and security needs of Enterprise customers without sacrificing performance or the user experience. Find out more information about system requirements, eligibility, how to place an order, supported environments, etc. on the dedicated page at pixlab.io/on-premise.

The PixLab Computer Vision team is pleased to announce the immediate availability of PixLab Annotate. A web based image annotation, labeling & segmentation tool for Machine Learning model training tasks and beyond...

Annotate Features Set:

• Rectangle, Polygon, Zoom & Drag labeling tool.
• Consistent JSON output accepted by most Machine Learning frameworks.
• Optimized for instance segmentation (Mask R-CNN, etc).
• Client-side persistent storage - No data transfer involved.
• Persistent & easy label management (Create, Modify & Delete).
• Full screen display & Snapshot capture.

At PixLab, we really believe that annotate is a great fit for data scientists, developers or students looking for a straightforward, online image segmentation and labeling tool for their daily machine learning model training tasks and beyond...

Annotate Homepage

• annotate.pixlab.io

Feature & Support Requests

• PixLab Github Repository

Developed by our colleague Mrad Chams from Symisc Systems and entirely powered by the PixLab OCR API endpoint.

Talkie OCR - A state-of-the-art OCR scanner that practically turn almost any images with human readable characters into text content which is in turn transformed into human voice in your native language & accent. Built in features includes:

• Automatically Recognize the Input Language & Speaks your Accent: Once the scanned image (Book page, magazine, journal, scientific paper, etc.) recognized & transformed into text content, you'll be able to playback that text in your local accent & over 45 languages of your choice!
• State of the art OCR processing algorithm powered by PixLab.
• Speaks over 45 languages with their accents.
• Built-in translation service to over 30 foreign languages of your choice.
• Built-in Vision Impaired Mode with the ability to recognize the input language automatically.
• Playback Pause & Resume at Request.
• Offline Save for Later Read & Playback.

• App Store Link: apps.apple.com/us/app/id1512795289
• Play Store Link: play.google.com/store/apps/details?id=net.symisc.ocr.img.speech
• App Website: i2s.symisc.net

The PixLab development team is pleased to announce the immediate availability of the PixLab API 1.9.72.

Since its launch on 2017, PixLab have already processed over 450 Millions of users contents whether static images, GIF or Videos Frames. This milestone release introduces new API endpoints, various minor bug fixes, processing speed improvements by up to 5% and many innovative features. Let's start with the one we are existed about in no particular order:

• Passports & ID Cards Scan: While documents scanning were introduced in earlier version of the PixLab API via the /docscan endpoint. This release pushes further the accuracy of the OCR engine. A 5MB raw Passport sample now takes less than 3 seconds to execute including face detection & extraction, MRZ (Machine Readable Zone) extraction and finally transformation of the Raw MRZ data into textual content. You can try out the accuracy of the Passport scanning engine using these Python and PHP scripts to see it in action.
• DNS infrastructure moved to Cloudflare for faster than ever response times.
• Full support for HTTP/2 and HTTP/3 (QUIC).
• Up to three layers of redundancy for the standard PixLab OCR engine for faster, accurate & guaranteed scan results.
• A fresh update of the adult & gore content detection ML model which is used to power the famous PixLab /NSFW API endpoint that have already analyzed over 100 millions of user contents with high accuracy.
• Face Detection (including facial landmarks extraction) & Emotion Pattern (including gender & age) extraction are now using the RetinaFace Model which scores the highest on the LFW dataset.
• The /docscan API endpoint now fully support scanning ID cards from Malaysia & Singapore and many other countries (at users request) as well the brand new India Aadhar ID card. Find out more information about Aadhard fully support via our blog announcement here.
• Finally, a brand new, high performance custom image processing layer written in C/C++ and powered by ImageMagick and our Embedded computer Vision Library SOD is integrated directly into our cloud API.

Pixlab customers are more than advised to take a look at The official API endpoints documentation, The Samples Page, The Github repository for additional information.

Finally, for potentially interested users, you are more than welcome to start a 7 days free trial to see the API in action. Simply head to the PixLab Dashboard and activate your free trial from there.