Facial mapping and analysis has been made simple with face recognition attendance software. Earlier, face recognition software was considered to be a thing of fiction but nowadays, it is used in a variety of applications. When we say face recognition software, our focus immediately shifts towards the face unlock present in our smartphones. It is one of the applications of the face recognition system but it is not limited to that.

Why face recognition attendance software?

Technological trends are changing everyday. The latest technology has features and has overcome the shortcomings of the precious one. Face recognition system is one among the latest technologies in the field of security systems. So it will best include these systems as part of security add ons, here are some of the reasons that proves the same.

Security: In comparison with the other biometric based recognition system, the face recognition attendance software offers more secure means of attendance. It is nearly impossible to replicate the face recognition system as it involves the recognition based on face.

Accuracy: It offers the most accurate results for the searches. Major companies consisting of Amazon, IBM and Microsoft sell their software for law enforcement purposes.

Timeliness: The services must be offered on time for the customers. People need not spend much time in front of the system. It is capable of recognizing multiple faces simultaneously making it a much accurate system.

Stages involved in Face recognition system

Face detection process

It is the process of finding the face in the image. The face detection system process does not include the detection system. Once the image is captured, it is sent in to the back-end system using HTTP based data requests. The image is saved along with detection log details and timestamp details. Golang and Mongo DB are used for storing data.

Analysis

The face is performed deep analysis techniques by mapping the distance between the eyes, nose, and mouth. The data found is called a “face print”, and is run against the face print to find an effective match. Since the COVID-19 outbreak, people are extensively using the mask so the face recognition algorithm must be equipped to identify faces present in the mask. The advanced face recognit ion software uses deep learning based on convolutional neural networks to recognize people with face masks.

Instant face recognition

The neural network based face recognition system is trained for different data sets. As part of the development process, the application is trained to recognize various faces of people belonging to different ethnicities. So that it is accurate to recognize faces quickly under real-time circumstances where there would be varying data sets to detect.

Numerous applications of face recognition systems

Checkin services: Contactless recognition systems can be used to verify people along with the existing database.

Access to buildings: It is used for access provision for buildings for entering hotels, events and meetings. People no longer need to go through the database to allow the person.

Conclusion

Face recognition employee attendance software will be the appropriate solution to include in corporates. The face recognition software has the capability to quickly recognize staff and mark their attendance. It is a viable solution to include for its security and accuracy aspects.