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Tag: facial recognition technology

4 Reasons to implement facial recognition technology right now

As this article series outlines, risk associated with human touch by the Covid 19 pandemic has underlined the urgent need for touch-free systems at workplace. Businesses are looking to adopt facial recognition system for attendance at workplaces. A facial recognition software is advanced enough today to recognize faces despite a difference in illumination and factors such as ageing. Today the technology is used in a number of sectors ranging from law enforcement and security to retail.

How facial recognition technology works

1- First, the facial recognition software captures your face as a picture or video.

2- Facial recognition algorithm “sees” faces as data. The software maps the geometry of your face. It focuses primarily on the space between your eyes and the distance between your forehead and chin. Next, it identifies landmarks that distinguish your face from others. Now, the software has built your facial signature.

3-Lastly,this ;signature’ of you is compared to a database to identify your face with accuracy.

Why use facial recognition technology?

  • Security: The technology has proved to be an effective law enforcement tool for governments. Additionally, the technology cannot be hacked, which makes it suitable for locking and unlocking devices such as computers and smartphones.
  • Faster processing: It takes just one second for face recognition to process. This has proved beneficial for companies as it enables them to quickly verify a person. This, combined with the foolproof nature of the technology makes it a great way for applications such as seamless payments and logging attendance at workplace.
  • Improved services: Smooth integration offered by facial recognition systems could enable various sectors to improve their services. For instance, facial recognition could replace OTP in banking. In retail, shopping centers that “know” their customers could offer a more seamless shopping experience. This is also true of airports.
  • Contact-less system: Face recognition provides a non-intrusive way of verifying identities. As the world recovers from Covid-19 pandemic, touch-less systems are poised to become more relevant and mainstream.

Despite its many advantages and successful early adoption by many sectors, some businesses have been reluctant to implement facial recognition technology. High costs of implementation and doubts about the system’s ability to detect changes such as illumination and aging process are points of concern.

Crafsol has been focused on developing solutions that bring cutting edge technologies at affordable price points. Facial recognition technologies developed by us are being used across sectors such as banking, retail, and others. In order to know more about how Crafsol’s facial recognition technology might help your business become better and more reliable, reach out to us at: .

Understanding the approaches to facial recognition technology

As the previous article illustrates, the need for touch-free identity authentication is more serious than ever. As questions surround the finger-touch bio-metric machines, businesses are looking at using facial recognition for attendance. In order to build a better understanding of this technology, let us take a look at different approaches used in building a good facial recognition software.

Approaches to facial recognition technology

Feature-based approach
In this approach, facial recognition software relies on mapping significant features such as eyes, nose etc to generate primary input data for face recognition. This approach works in three stages: in the first stage, the intensity of the image is calculated in terms of features. In the second stage, the image is represented as a series of graphs. Here, the nodes in the graph represent features information while links in the graph represent relation between the features. In the third and final stage, this data is matched with a database to identify the face correctly.

Holistic approach
In the holistic approach to face recognition the whole head is considered for input. While feature-based approach considers face as a flat plain, holistic approach creates a model of the entire head. This technology sees the whole head as a cylindrical volume. Further on, it takes into account the possibility of movement. This approach too marks a number of feature points on the face and then adjusts these points according to the way the face rotates.

Hybrid approach
The hybrid approach to facial recognition technology is simply the combination of the two other approaches in face recognition. This approach helps scientists overcome the shortcomings of other individual approaches. According to some studies, this approach can work in two stages called training and classification.

In the training stage, facial recognition algorithm extracts various feature points from faces using a combination of technologies such as Principle Component Analysis (PCA) and Independent Component Analysis (ICA). After this, these extracted features are trained in parallel and partitioned into different face classes using Back-propagation neural networks (BPNNs) In the classification stage, the images are classified into different face classes using a combination of various algorithms.

While these are the broader approaches to face recognition, there are other specific techniques to design algorithms. These techniques include Eigenface, Neural network, Fisherfaces, Elastic bunch graph matching, and Geomatrical feature matching.

At present, facial recognition techniques used by social media companies are capable of identifying faces with 97% accuracy. However, new challenges now loom on the horizon for facial recognition technology.

The new challenge for facial recognition algorithms

However, with masks becoming ubiquitous, identifying faces wearing masks is the new challenge for facial recognition tech. recently, a company in China has claimed that it has resolved the issue.

The new challenge for facial recognition algorithms

There seem to be two approaches to solving this problem. First, making algorithms adapt at guessing what a face could look like without wearing mask. Second, deleting a part of the picture, so that the algorithm is designed to recognize half the face itself accurately. Chinese researchers working on this issue claim that the first approach requires loading into the system, around 6 million pictures of people without masks, and then some pictures without masks.

Despite the new challenges, there is recognition within the industry that the time for use of face recognition technology at workplace has arrived. The recent Covid-19 pandemic has underlined the need for face recognition to replace biometric touch pads and other systems that involve touch.

Crafsol has been working to make advanced facial recognition technology available at affordable prices to businesses across India. Early adaptation of this technology for functions such as logging employee attendance could ensure a hassle-free and safe workplace for all. If you want to explore how this technology could help your business, reach out to us at…..

Is facial recognition system for attendance finally here ahead of its time?

Given how Covid 19 pandemic has rendered human touch a potential health threat, the use of bio-metric machines at workplaces has come under scanner.

Consider this: You have a steel plant which has thousands of workers. The plant has now restarted after the pandemic. the bio-metric machine is somewhat of a risk considering the number of workers. However, a reliable alternative is needed to check impostors entering the plant in place of actual workers.

Could facial recognition system be an alternative to bio-metrics ?

As facial recognition technology adoption by mobile companies demonstrates, facial recognition is emerging as a hands-free way to gain access. However, facial recognition algorithms must still overcome some significant challenges to become mainstream.

Challenges before facial recognition technology

Costs: Market research by consulting giant Gartner outlines how cost hinders the adoption of facial recognition technology. Advanced technology that is used by the likes of government agencies is high in cost as well. On the other hand, cheaper options in this field often do not live up to the expectations of customers. This leads to many customers avoiding buying facial recognition technology.

Lack of standards: There is no set of specific standards which would enable customers to evaluate the solutions that vendors have to offer. Hence, decision-making becomes difficult. Additionally, vendors might throw in terms such as deep learning, artificial intelligence etc and further confuse the customer.

Lack of awareness: Facial recognition technology is often seen to intrude into privacy. At this point, an educated debate with the customers around the issues of privacy often becomes difficult.

Despite the challenges, early adoption of facial recognition technology has already begun…

Despite these challenges, facial recognition softwares are emerging as a useful tool. Rajiv Gandhi International Airport at Hyderabad recently became the first airport in India to initiate facial recognition. After enrolling into the programme, passengers can now pass seamlessly through all touchpoints at the airport for further departures.

Elsewhere, medical colleges in Japan are already using facial recognition technology to log attendance in classes.

In the face of recent circumstances, businesses across India are considering deploying facial recognition for logging attendance. Resolving the affordability factor of facial recognition technology has been a key priority at Crafsol. The company has a decade of experience in providing smart facial recognition systems to sectors such as banking and retail. To know more about how Crafsol’s facial recognition technology can help you build a better and safer workplace, reach out to us at:

https://crafsol.com/contact-us/
Or give us a call at +91-20 65427680

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