Unlike other identification solutions such as passwords, verification by email, selfies and images or fingerprint identification, Biometric facial recognition uses unique mathematical and dynamic patterns that make this system one of the safest and most effective o
Door automation through face Recognition
Moreover, technology systems can sometimes vary when it comes to facial recognition, but the general functioning is as follows.
To begin, the camera will detect and recognize a face, either alone or in a crowd. The face is best detected when the person is looking directly at the camera. The technological advancements have enabled slight variations from this to work as well.
Next, a photo of the face is captured and analyzed. Most facial recognition relies on 2D images rather than 3D because it can more conveniently match a 2D photo with public photos or those in a database. Distinguishable landmarks or nodal points make up each face. Each human face has 80 nodal points. Facial recognition software will analyze the nodal points such as the distance between your eyes or the shape of your cheekbones.
The analysis of your face is then turned into a mathematical formula. These facial features become numbers in a code. This numerical code is called a faceprint. Similar to the unique structure of a thumbprint, each person has their own faceprint.
Your code is then compared against a database of other faceprints. This database has photos with identification that can be compared.
According to records FBI has access to more than 641 million photos, including 21 state databases such as DMVs. Another example of a database that many have access to is Facebook’s photos. Any photos that are tagged with a person’s name become part of the Facebook database.
The technology then identifies a match for your exact features in the provided database. It returns with the match and attached information such as name and address.
Aside from unlocking your smartphone, facial recognition brings other benefits to the companies.
The first thing to start with is surveillance. With the help of facial recognition, it will be easier to track down any burglars, thieves, or other trespassers.
On the governmental level, facial recognition can help identify terrorists or any other criminals with the help of the face scan only. The additional bonus is the fact that one cannot hack the technology: there is nothing to steal or change, like in case of a password, for example.
The process of recognizing a face takes a second or less — and this is incredibly beneficial for the companies.
In the era of constant cyber attacks and advanced hacking tools, companies need a technology that would be both secure and fast. Considering that facial recognition is almost instant, it grants a quick and efficient verification of a person. In addition, it’s hard to fool this technology so this is another bonus.
Before, security guards had to perform manual identification of a person that took too much time and did not boast high accuracy. But today, facial recognition is completely independent in the identification process and not only takes seconds but is also incredibly accurate.
The 3D facial recognition technology and the use of infrared cameras significantly boosted the level of accuracy of facial recognition and made it really hard to fool.
With the help of this technology, the government can track down the criminals. But at the same time, it can actually track down people like you anytime, anywhere.
So even though facial recognition indeed brings benefits, there is still an awful lot of work to be done before the technology is 100% used fairly and in accordance with human rights for privacy.
Artificial intelligence technology requires massive data sets to “learn” in order to deliver accurate results. And such data sets require a powerful data storage.
So if you are a small or medium-sized company you simply may not have the necessary resources to store all the data. And that might be a problem.
Facial recognition is a powerful technology but it has to be used wisely. On one hand, it brings immense advantage to the companies and end-users, helps them enhance their security and track down the trespassers.
The main idea of using PCA for face recognition is to express the large 1-D vector of pixels constructed from 2-D facial image into the compact principal components of the feature space. This can be called eigenspace projection.
The image is a combination of pixels in rows placed one after another to form one single image each pixel value represents the intensity value of the image, so if you have multiple images we can form a matrix considering a row of pixels as a vector
The goal of PCA is to identify patterns in a data set, and then distill the variables down to their most important features so that the data is simplified without losing important traits. PCA asks if all the dimensions of a data set spark joy and then gives the user the option to eliminate ones that do not.
Principal Component Analysis (PCA) provides enhanced accuracy in features based image identification and classification as compared to other techniques. PCA is a feature based classification technique that is characteristically used for image recognition.
With three dimensions, PCA is more useful, because it's hard to see through a cloud of data. In the example below, the original data are plotted in 3D, but you can project the data into 2D through a transformation no different than finding a camera angle: rotate the axes to find the best angle. To see the "official" PCA transformation, click the "Show PCA" button. The PCA transformation ensures that the horizontal axis PC1 has the most variation, the vertical axis PC2 the second-most, and a third axis PC3 the least. Obviously, PC3 is the one we drop.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| IPC-A22EP-A Camera | Equipment | 1 | 6000 | 6000 |
| FTDI Board | Equipment | 1 | 3401 | 3401 |
| Relay Module | Equipment | 1 | 900 | 900 |
| Solenoid Lock 12V | Equipment | 2 | 1500 | 3000 |
| Raspberry pi 4 Chip | Equipment | 1 | 24999 | 24999 |
| Jumper Cables | Miscellaneous | 3 | 1600 | 4800 |
| Total in (Rs) | 43100 |
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