Difference between face detection and facial recognition Technology in Hindi !! face detection !!

Difference between face detection and facial recognition Technology in Hindi !! face detection !!
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In our industry, the terms face detection and face recognition are sometimes used interchangeably. But there are actually some key differences. To help clear things up, let’s take a look at the term face detection and how it differs from the term face recognition.


The definition of face detection refers to computer technology that is able to identify the presence of people’s faces within digital images. In order to work, face detection applications use machine learning and formulas known as algorithms to detecting human faces within larger images. These larger images might contain numerous objects that aren’t faces such as landscapes, buildings and other parts of humans (e.g. legs, shoulders and arms).

Face detection is a broader term than face recognition. Face detection just means that a system is able to identify that there is a human face present in an image or video. Face detection has several applications, only one of which is facial recognition. Face detection can also be used to auto focus cameras. And it can be used to count how many people have entered a particular area. It can even be used for marketing purposes. For example, advertisements can be displayed the moment a face is recognized.


While the process is somewhat complex, face detection algorithms often begin by searching for human eyes. Eyes constitute what is known as a valley region and are one of the easiest features to detect. Once eyes are detected, the algorithm might then attempt to detect facial regions including eyebrows, the mouth, nose, nostrils and the iris. Once the algorithm surmises that it has detected a facial region, it can then apply additional tests to validate whether it has, in fact, detected a face.


One of the most important applications of face detection, however, is facial recognition. Face recognition describes a biometric technology that goes way beyond recognizing when a human face is present. It actually attempts to establish whose face it is. The process works using a computer application that captures a digital image of an individual’s face (sometimes taken from a video frame) and compares it to images in a database of stored records. While facial recognition isn’t 100% accurate, it can very accurately determine when there is a strong chance that an person’s face matches someone in the database.

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