Do you know about Face Attendance System?

Our hi-tech world has brought us so many machinery which made our lives quite easy. Amongst this equipment, one popular technique is a biometric attendance system and the Face recognition attendance system is one of them. This advanced face recognition attendance biometric system enrolls the unique and permanent facial fine points of employees and records them in the database as stencils. Once the enrollment process is complete, you just need to look at the camera to verify your identity and the face recognition attendance system automatically marks your attendance on behalf of you. It is a facial recognition attendance system that ensures contactless authentication and identifies the user's face in less than a second.

How Face attendance system works?

This section describes the software algorithm for the system. The algorithm consists of the following steps-

  • v Image acquisition>
  • v Histogram normalization
  • v Noise removal
  • v Skin Classification
  • v Face Detection
  • v Face Recognition
  • v Attendance

In the very first step image is captured from the camera. There are illumination effects in the captured conditions and some noise which is to be removed before going to the next steps. Histogram normalization is used for contrast enhancement in the spatial domain. The median filter is used for the removal of noise in the image. There are other techniques like FFT and low pass filter for noise removal and smoothing of the images but the median filter gives good results.

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Compared to other Biometric systems

One key advantage of a facial recognition system that it is able to person mass identification as it does not require the cooperation of the test subject to work. Properly designated systems installed in airports, multiplexes, and other public places can identify individuals among the crowd, without passers-by even being aware of the system.

However, as compared to other biometric techniques, face recognition may not be most reliable and efficient. Quality measures are very important in facial recognition systems as large degrees of variations are possible in face images. Factors such as illumination, expression, pose and noise during face capture can affect the performance of facial recognition systems.

Compared to other Biometric systems

Among all the Biometric systems, facial recognition has the highest false acceptance and rejection rates, thus questions have been raised on the effectiveness of the face recognition software in case of railway and airport security. Besides the pose variations, low-resolution images are also very hard to recognize. This is one of the main obstacles to face recognition in surveillance systems.

Face recognition is less effective if facial expressions vary. A big smile can render the system less effective. There is also inconsistency in the datasets used by researchers. Researchers may use anywhere from several subjects to scores of subjects and a few hundred images to thousand of images. It is important for researchers to make available the datasets, they used to each other, or have at least a standard dataset.

Data privacy is the main concern when it comes to storing biometrics data in companies. Datastores about-face or biometrics data in companies. Datastores about-face or biometrics can be accessed by the third party if not stored properly or hacked. "Hackers will already be looking to replicate people's faces to trick facial recognition systems, but the technology has proved harder to hack then fingerprint or voice recognition technology in the past."

Use of Facial recognition system

The most common field where the Facial Recognition system is used nowadays is Face attendance. Earlier, it used to be very hectic for an individual to mark attendance of students or employees and also there was always the possibility of error. But now with the new Facial recognition system technology, it has become very easy to identify a person and to mark his attendance.

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