A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database.

Some facial recognition algorithms identify faces by extracting landmarks, or features, from an image of the subject's face. For example, an algorithm may analyze the relative position, size, and/or shape of the eyes, nose, cheekbones, and jaw. These features are then used to search for other images with matching features. Other algorithms normalize a gallery of face images and then compress the face data, only saving the data in the image that is useful for face detection. A probe image is then compared with the face data.One of the earliest successful systems is based on template matching techniques applied to a set of salient facial features, providing a sort of compressed face representation.

Recognition algorithms can be divided into two main approaches, geometric, which looks at distinguishing features, or photometric, which is a statistical approach that distill an image into values and comparing the values with templates to eliminate variances.

Facial recognition is alive and flourishing. It’s used in many broad areas, including social networking, photo editing, security, law enforcement, casinos, and in odd places that you might not expect. For example, the dating website FindYourFaceMate.com based matchmaking around the principle that people with similar facial features are attracted to each other, using facial recognition to match user photos, and DoggelGanger.com matches potential dog owners with canines that look like them. Face recognition cameras scanned all the fans walking through the turnstiles at Super Bowl XXXV, now referred to as the Snooper Bowl, running the scans against a database of criminal mugshots. That was a decade ago, when the internet was still in its relative childhood. We’re in an age now when Facebook collects 100-page dossiers on all of us, when ad networks track everything we do online, when companies buy and sell our contact information: the street we grew up on, the names of our family members, aerial shots of our homes.


Companies give two main reasons for using facial recognition technology: it helps with security, and it makes photo editing and sharing easier. On the security side, law enforcement officials have argued that facial recognition can help find missing people, identify criminals in a crowd, preempt terrorists from boarding planes with fake passports. It’s also used for private security in casinos to identify card counters and kick them out before they can win too much. Casinos also say their systems identify people with gambling addictions who’ve asked casinos to forcibly remove them if they can’t stop themselves. Even supermarket security uses facial recognition: one grocery chain in the UK uses facial recognition to stop underage customers from buying alcohol.


On the photo sharing side, facial recognition can scan albums for faces and either suggest tags or automatically tag people. You’ll already find it in Apple’s iPhoto, Google’s Picasaweb, Microsoft’s Windows Live Photo Gallery, and other photo editors. It also collects information on different people’s faces through existing tags: the more tags, angles, lighting types, hairstyles, and other details in your photos, the better the software’s ability to pick you out in other photos. It’s one thing to confine this technology to the photos on your own computer, but things get more complicated when the internet gets involved.


So the day will never far away when in each and every thing such techniques can be applied right from booting up of personal computer with starting of car

The accuracy rate is 99.31% on still frontal face images. Changes in lighting, face positioning, makeup, hairstyle, facial hair, glasses, and other accessories decreases the accuracy rate sometimes.

Facial recognition has its benefits, especially for certain groups and activities.

Benefit 1: Easier photo organization

Facial recognition boasts the end of long tagging sessions. If you upload all your photos and facial recognition software identifies and tags your friends, most of your work is done. Even less powerful software that only identifies and suggests tags, rather than tags automatically, can save a lot of time.

Benefit 2: Greater access to information

If a picture’s worth a thousand words, then a picture associated with a database of internet data is worth an encyclopedia. You could learn all about someone with a single photo. This could be helpful for people who need a lot of information in a short period of time: for example, if you want to learn about a potential date, get some background on a job applicant, or find a long-lost friend or relative.

Facial recognition applications could have special significance for those with prosopagnosia, also known as face blindness. This condition makes it difficult or impossible to identify people. You may have met someone a hundred times, but if you have severe prosopagnosia, you won’t recognize him or her. And for those of us who just have trouble remembering faces, this wouldn’t be a bad thing, either.

Benefit 3: Criminal identification

If you have a database of known criminals, you can use facial recognition to cross-reference those faces against other databases of faces. With the right technology, you could scan a public area for wanted felons, for example, or see if any of them have signed up for Facebook. Even if you can try to hide from a criminal past by changing your name, it’s much harder to change your face. Thus facial recognition is already a valuable tool in law enforcements’ arsenal, and it’s only becoming more important.

Benefit 4: Money, money, money

If you’re an advertiser, there’s money in facial recognition. Photos are the key to unlocking a vault of valuable personal information. The more they know about a person or a segment, the better they can tailor their ads to target them, and the more successful these ads will be. Your data is worth its weight in gold.

GSM (Global System for Mobile Communications, originally Groupe Spécial Mobile), is a standard set developed by the European Telecommunications Standards Institute (ETSI) to describe technologies for second generation (2G) digital cellular networks. Developed as a replacement for first generation(1G) analog cellular networks, the GSM standard originally described a digital, circuit switched network optimized for full duplex voice telephony. The standard was expanded over time to include first circuit switched data transport, then packet data transport via GPRS (General Packet Radio services). Packet data transmission speeds were later increased via EDGE(Enhanced Data rates for GSM Evolution). The GSM standard is more improved after the development of third generation (3G) UMTS standard developed by the 3GPP. GSM networks will evolve further as they begin to incorporate fourth generation (4G) LTE Advanced standards. "GSM" is a trademark owned by the GSM Association.


The GSM Association estimates that technologies defined in the GSM standard serve 80% of the world's population, encompassing more than 6 billion people across more than 212 countries and territories, making GSM the most ubiquitous of the many standards for cellular networks.

I got the solution to read tamil sites in our Android devices

Install Opera mini.
In the browser address bar, type in "opera:config" (without the quotes) and then go. This will take you to the opera settings page.

Find the option that says "Use bitmap fonts for complex scripts" . The default is "no" for this option. Change this option to "Yes" and click save.

Once this is done. u can read the tamil fonts in the browser.

I got the opera mini from onlyandroid.mobihand.com

Good Luck