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How the US Department of State checks applications and photos of participants of the Green Card Lottery

The Green Card Lottery since its inception and up to the present has been and remains the easiest way to immigrate to the USA. For the millions of people participating in the DV program, winning a green card in a lottery game is the only immigration they can count on. And here it is important not to miss your chance because of the annoying little things - mistakes in the questionnaire or the wrong photo. Photos when checking out the questionnaires are given HUGE attention. How exactly the photos are checked and why the instructions should be strictly followed, explains the Florida Center for Assisting Compatriots Median.

Фото: Depositphotos

Naturally, each participant wants to know how the drawing process takes place, whether the winners are really randomly selected, and most importantly, how to increase your chances of winning.

The draw process itself is nothing interesting. A computer really randomly selects a certain number of winners from the region’s common base, all over the world - from 100 to 150 thousands. Considering that there are only 50 thousands of visas, a rather large supply is being made, which will cover the screenings in the future - “athletes” who play to test their luck; people who, having calmly estimated the pros and cons of immigration, will refuse to continue the process; convicted; not passed medicine; those who cannot collect the necessary documents or enough money; disqualified due to errors and fraud and so on.

Also, in addition to all these people, out of 100-150 thousands of initially selected winners will be eliminated those who submitted not one, but several applications.

The very first check when applying for a green card lottery

From 7 to 15 millions of applications are submitted annually to participate in the green card lottery (depending on the participating countries). It is clear that processing and checking such a quantity of documents manually is an ungrateful job, fraught with a large number of errors. For this reason, almost the entire processing process is automated and entrusted to special computer programs.

At the time of filing an application through the site dvlottery.state.gov, the built-in validator checks whether all the necessary fields of the questionnaire are filled in and whether the attached photos correspond to the specified technical parameters. This is the very first technical check. She will miss any applications formally corresponding to the rules. For example, it is possible to submit a questionnaire by a person named Yyyyyyy Xxxxxxx with a photograph in which there is no image of a person. If this photo is 600 by 600 pixels in size, a .jpeg file, less than 240 kilobytes, color with 24-bit depth - all technical parameters of the file are met, the application will be accepted, a Confirmation Number will be issued.

However, this participant Yyyyyyy Xxxxxxx will never receive notification of a win - his application will be rejected at the next stage of verification and she will not accept participation in the green card drawing.

Verification of applications for the green card before the drawing

The US State Department does not report on which day the green card lottery is being drawn. The exact date of the drawing is considered to be detail, not mandatory for publication. However, there is evidence to conclude that the draw of the green card lottery is held in early December.

Thus, it can be seen that it takes about a month from the moment the applications for participation in the lottery are finished until the winners are determined. During this month, the submitted questionnaires are sorted and prepared directly for the rally.

Green card lottery draw and screening of garbage applications

In fact, not one general draw is held, but six separate ones - in each of the six regions into which the world for the DV-lottery program is conditionally divided. For each region, a certain quota of winning people is calculated, the sum of these six quotas gives the total number of winnings - 100-150 thousand.

At the time of the draw, all regional applications are randomly assigned new numbers (case numbers).

Then each application is checked for compliance with the technical requirements of the rules of the DV-lottery. The program takes the application with the number 1, checks it and gives a conclusion about its compliance with the requirements. Then goes to the application number 2 and so on. If the program detects an application that does not correspond to the specified parameters, it marks it as “junk” and skips its number — the person who submitted it will not see the notification of the win. So the program checks applications in a row until the quota is filled with “good” numbers.

Since no supporting documents are attached to the questionnaires when submitting an application, it is not possible to establish the accuracy of the data specified at this stage of the verification. A person may well be called Yyyyyyy Xxxxxxx. Therefore, in the future, only submitted photos are checked.

Each image file is analyzed, it establishes whether the person is depicted in the photo and whether its image meets the compositional requirements.

The area of ​​the image in which the head should be located is determined by the rules — the program imposes a virtual mask on this area, which is the average display of the main parts of a human face: eyes, nose, lips, etc. If the parameters of the analyzed area match according to certain criteria with a mask, the photo is defined as containing a face image. At the same time, the program checks that it is a photograph in front of it, and not, for example, a watercolor drawing. Image quality is also checked.

At this stage, questionnaires with pictures of cats, cars, clouds, black squares, etc. are discarded. Such questionnaires are usually filed by people in order to see how the site works, to practice before submitting their present application.

Verification of compliance with compositional requirements

The rules set fairly stringent requirements for the image of a person in a photograph: the size of the head, the eye level, the position of the head - its tilt and rotation, the background color are strictly stipulated. In this case, nothing is said about the ears, shoulders, hair, beard and mustache, make-up.

Accordingly, we can expect that the program will check only what has been said.

If the head in the photo is more or less than what is needed, turned to the right or left, raised or lowered, the eyes are higher or lower than it should be - the application will be rejected during the check. If the hair is not visible ears, shoulders are not on the same level, mustache and beard hide your mouth, but the proportions are met and the person looks directly into the camera - the application will be deemed fit.

During this check, the correctness of the background and the absence of shadows on it are evaluated - the contours of the head should be clearly defined against the background. Shadows on the face can cause disqualification if the program because of them can not recognize some parts of the face.

Why is it so important for the program that certain parameters are absolutely respected (such as the height of the eyes and the size of the head), while it does not pay attention to others?

Preparing for the first stage of facial recognition

The statement will not be a discovery that in order to increase your chance of winning the lottery, a participant must submit several applications. It is forbidden by the rules, but the temptation is great, and many people (and intermediary organizations) resort to various tricks to circumvent the ban.

The above illustration shows the same girl, but with a different hairstyle. In order for the computer to understand that it is the same person, face recognition technology is used.

When checking photos submitted for participation in the lottery of green cards, several steps of machine recognition of faces are used. Each subsequent recognition algorithm is more complicated than the previous one, therefore the number of analyzed images decreases with each step - until the result remains, those photos about which the program with almost 100-percent certainty can say that the same person is depicted on them.

Recognition is realized on the basis of FaceIt technology developed by Visionic. The main developer and program manager is Dr. Joseph Atik. In June 2002 of the year, this company became part of Identix Inc, which since August 2006 of the year, after merging with Viisage Technology, began to work under the brand L-1 Identity Solutions, in July 2011 was acquired by Safran concern and is now known as MorphoTrust.

Identix Corporation, which historically specialized in fingerprint recognition, acquired Visionic with its facial recognition technology, in March 2004 absorbed Delean Vision, which developed a method for analyzing and comparing human skin textures. This acquisition made Identix a world leader in the field of human identification with a complex of three areas - fingerprints, face, skin.

In September 2004, the company Identix Inc. won a tender to supply the US Department of State an automatic biometric identification system, as well as to work on the deployment, integration into the visa system, and further support of the selected platform. Identix offered DoS its ABIS 3.0 (Automated Biometric Identification System) platform implemented using FaceIt G6 face recognition technology.

According to the terms of the contract, the created system was supposed to provide initial registration of about 35 million available visa images; processing about 8 million new visas in the first year of the contract; processing annually at least 10 million e-Diversity Visa applications; processing speed up to 2000 comparisons per hour.

The FaceIt technology is used by the State Department (DoS) to test people applying for any entry visas to the United States. What specific recognition methods are used can be seen from the technical characteristics of the FaceIt technology.

Initially, in the interests of DoS, FaceIt G6 technology was used, which applies three stages of analysis when comparing individuals. Since 2010, the ABIS platform has been upgraded to a new version of FaceIt - G8, supplemented by another step, the Hierarchical Face Graph Comparison Algorithm (HGM) - this direction was developed by Morpho, a division of the Safran concern, which L1 entered. It is logical to assume that DoS has applied this update in the programs it uses.

(We should not forget about the existence and the fifth step of recognition - the visual identification of a person by a person).

In order for the system to successfully recognize faces in photographs, the images must be specially prepared.

FaceIt works with images compliant with ISO / IEC 19794-5.

Each photo attached to the application for participation in the green card lottery is considered and its suitability for the recognition process is determined, and the following parameters are evaluated:

  1. Is the head size large enough?
  2. Cropping - is the face completely visible on the image?
  3. Centering - is the face sufficiently centered?
  4. Exposure - is the image not overexposed or underexposed?
  5. The eyes are clearly visible - are there glasses on the person, and if so, are the eyes visible or hidden?
  6. Focus - is the image well focused?
  7. Compression - Was the image not overly compressed to remove skin details?
  8. Texture - Does the surface of the skin contain textures suitable for use in face recognition?
  9. Resolution - Does the image resolution exceed the minimum measured in pixels between the eyes?
  10. Faceness - is it possible to call the object found on the image a human face, or not?

At the stage of preparation, the photographs normalize - the computer rotates the pictures so that their eyes are placed strictly horizontally (aligns the face with the vertical axis) and crop the image to a new size, cutting off all unnecessary. Pictures are cropped so that the distance between the centers of the eyes is the same in all images, the brightness and contrast of the pictures are aligned.

Electronic face recognition on photos

Electronic recognition is applied only to those winning bids that were deemed fit at the previous verification stages and the photos of which were successfully normalized.

First pass identification - Vector comparison (VFA)

At the first recognition stage, the vector comparison algorithm (Vector Feature Analysis - VFA) is applied.

The essence of this recognition method is that the program presents each analyzed normalized face image as a linear combination of other pre-created special images, the so-called eigenvectors or eigenfaces (“eigenfaces”). The result is a code containing information about this combination. This encodes every image that requires verification.

Very simply “own faces” (“eigenvectors”) can be represented as a set of some standard face components, obtained by statistical analysis, subsequent sampling and processing of a large variety of images of different faces. When using this method, it is taken as an axiom that any human face can be made up of an “average person” (a component that is the same for all persons) by adding to it a certain number of certain “own persons”. Most individuals can be obtained by adding a small number of "own persons".

Comparing then the obtained sets of eigenvectors, the system concludes that the original images are similar or different.

Each file with a code, or template, is a simple list of applied own persons (and the percentage expression of the contribution of each person to the image built from them) and has a very small size, so you cannot restore the face image using only the data of this template alone. However, due to the small size of the template files, comparing them with each other is very, very fast.

After all the template files are ready, the program compares the first winning application with all non-garbage files. It compares the templates obtained from the photos at the coding stage, evaluating the coincidence of the codes as a percentage. If the coincidence of the code being checked with any other does not exceed a certain value, the program concludes that no duplicates were found for the application.

Then the program proceeds to check the next application, also checking the photo code from it with all other codes of all photos from all submitted valid applications. So, one by one, the program checks all applications won in the lottery of green cards.

If the computer detects that the match of the codes of the two compared photos exceeds the threshold value (this value is one of the adjustable parameters of the identification system), the program makes a note about it and continues checking the code under study.

Thus, as a result of the first recognition pass, pairs (or triples, fours, etc.) of photographs are obtained, which the system suspected of showing the same person.

The vector comparison method is one of the most “ancient” methods used for face recognition. It is extremely demanding that all analyzed images are strictly normalized. Significant errors in the decision on the similarity of the compared persons, characteristic of this method, due to the small number of eigenvectors used, force it to be used only as the roughest tool, the basis for the further search for duplicates.

Second identification pass - Algorithm for comparison of hierarchical face graphs (HGM)

Hierarchical Graph Matching (HGM) is an algorithm for comparing individuals based on an analysis of the location of control nodes and the distances between them.

On the face, there are many, over 2000 points, starting from the centers of the eyes, nose bridge, tip and wings of the nose, left and right corners of the mouth and so on, which, when connected together, form the so-called graph, or mask, individual for each face. The distances between the points are alternately recorded in a file, encoding the image of the face and making it suitable for mathematical comparison.

This method of analysis does not depend on the texture of the face, exploring only its shape. Created mathematical models are built on the principle “from large to small”, which allows to significantly speed up the file comparison process.

The HGM algorithm shows fairly good recognition results in relation to the green card lottery program, where strictly normalized high-quality images are analyzed.

The third identification pass - Analysis of local differences (LFA)

Local Feature (Local Feature) is a portion of the image, which differs from other neighboring neighboring areas. The site may vary in intensity, color or texture, but does not have to be localized precisely by this change. Local differences may be points, edges, small parts of the image.

The LFA procedure describes a multitude of local interconnected sensory fields defined at each point of the virtual receptor grid superimposed on the face image. These fields are different from each other, optimally stacked in the original image, and at the output they differ as much as possible. The algorithm for creating files describing the dependence of these fields and then comparing these files is the basis used for checking photos on FaceIt's green card systems.

During the LFA, the program recognizes and evaluates many local differences in the facial structure image, again creating an encoded file. The system compares the created encoded files and notes those whose degree of coincidence is higher than a predetermined threshold.

One of the factors that impede the identification of persons is their variability depending on facial expressions. Even a small half-smile sets in motion a large number of facial muscles, while almost all distances between control points of the face change. The LFA method, analyzing the differences in the local areas of the face, which are moreover determined with a large excess, is practically free from the problems associated with facial expressions.

Fourth Identification Pass - Facial Surface Texture Analysis (STA)

Surface Texture Analysis (STA) should be understood as a combination of technologies and methods of identification using photographs that allow a sufficiently detailed examination of the skin texture of recognizable faces. Accordingly, it is the quality of the images that is of paramount importance for successful recognition.

The STA is used as a further development of the method of analyzing local differences, which makes it possible to use for comparison even smaller details that the surface of any person’s skin abounds in.

As a rule, a facial area free from excessively dense vegetation is analyzed - from the bottom of the eyes to the beginning of the upper lip.

In short, the STA method can be described as follows: first, the average brightness of each pixel is determined as the average gray scale of the pixels surrounding it. Then, the image of the face, by comparing the gray scale values ​​of pixels in their average brightness, is converted into a binary image with 1 or 0 values ​​assigned to those pixels whose average brightness is higher than the specified gray value boundary.

Then the selected face zone is divided into small blocks. For each block from the first image being compared, the system searches for the corresponding block in the second image, which is best matched with the compared block.

After that, the continuity of neighboring blocks is estimated. If the relative change in the positions of a pair of neighboring blocks is below a predetermined threshold, they are considered as continuous. The more continuous pairs of blocks, the greater the likelihood that the analyzed images belong to the same person. This probability can be formulated as a function of the number of continuous pairs of blocks.

Analysis of the surface texture requires, in comparison with other recognition methods, more time for calculations, therefore it is applied at the final stage of identification to those images for which there are reasonable grounds to be considered to belong to the same person. According to the developer, the use of the STA method, as an addition to the LFA, increases the recognition accuracy by 20 — 25%, making it possible to confidently distinguish even identical twins.

Recognize photo retouching for DVFor any inquiries, We're here to answer you.lottery

When checking applications for participation in the lottery of green cards, in order to prevent changes to the images in photographs using special graphics programs and other technical means, retouching is used.

The instruction for the green card lottery directly says that the retouching of the submitted photos is prohibited - applications that have shown any changes in the photos (show manipulation in any way) will be disqualified.

To detect retouching (the term “retouching” here means any changes to a photo, except cropping), special programs are used that use a combination of several algorithms when looking for changes — from color transformations to overlaying various filters and recognizing continuity of chains of blocks of pixels generated during compression images in jpeg, before analyzing jpeg-file code.

When making any changes to the photos, it should be remembered that, with high probability, retouching will be detected. Of course, you can try to make it difficult to detect retouching by printing on paper and scanning modified photos, photographing a monitor screen with a retouched image and similar tricks, but you need to understand that technologies used for testing may include tools to protect against such manipulations.

The result of checking photos for the lottery green cards

The computer cannot give a definite answer whether the same person is depicted in two different photographs or not. He can only estimate the probability of such a coincidence (of course, the probability can approach 100%). However, the final decision is always made by a person.

In the KCC, for each winner, a case (case) is started up, where the documents sent and the results of the checks are collected. If, based on the result of the verification of the photographs, duplicates are found in the application (the suspicion that these are duplicates exceeds a certain value), all these suspicious applications are also included in the case, an entry is made in the case description file, and a red label is attached to the paper file with the case the reasons.

The completed case is sent to the consular section where the interview will take place. During the interview, the consul will evaluate all the circumstances of the case, get acquainted with the results of the verification of photographs and visually compare the suspicious forms found, seeing a living person in front of him, the applicant. The result will be a decision - whether there was a violation of the rules, whether the applicant submitted several questionnaires, or not. Accordingly, the consul will either approve the issuance of the visa, or will refuse.

In the first year of the system's operation (DV-2006), the face recognition system among the winners detected a fraudulent 5221 application.

Cheating a duplicate finder on a green card lottery

Submission of several applications by one person is a violation of the rules of the lottery, leading to the automatic disqualification of the applicant.

For a lie to the consul under oath for an interview, you can get a life ban on entering the United States.

The consul, seeing in your case several applications filed with different photos recognized by the verification program, will certainly take an interest in the circumstances of the incident. If a person starts to lie, it will lead to a denial of a visa, and a life ban on entry.

The problem is that the applicant cannot know for sure why the consul asks about it - does the program really recognize its applications, or does the consul ask a simple ordinary question.

Based on this, the methods of cheating the recognition system can only be talked about theoretically, for research purposes, and also in order not to accidentally do something forbidden.

Online registration for the lottery Green Card 2021 It began on October 2 2019 of the year in 12: 00 Eastern Time and will continue until 12: 00 5 on November 2019 Eastern Time. ForumDaily has prepared all the details and tips for filling out the questionnaire for you. here.

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