Passport Image Research Articles

Catching wanted people at the border: prospective person memory and face matching in border control decisions

ABSTRACT Border control officers may be on the lookout for wanted people while they verify that travellers match their passport photos. We developed a novel experimental paradigm to investigate whether people are more likely to report that someone is wanted if they also believe that person is using a fraudulent passport. In two experiments, undergraduate students assumed the role of a border control officer and completed multiple “shifts” of a face matching task designed to simulate a passport verification check. Before each shift participants viewed posters of wanted people and were instructed to report any sightings if a wanted person appeared in any of the images during the passport check. Participants were more likely to say an individual was wanted if they also believed the person did not match their passport image. In addition, the accuracy of wanted person sightings was reduced for trials with nonmatching passports compared to trials with matching passports. This suggests wanted people with matching passports were easier to spot because participants had an additional image to compare with their memory of the person in the wanted poster.

Generating and Detecting Face Morphing Using Texture Techniques

Biometric forms major and very effective role nowadays in many fields such as health, reliability, devices, phones, banking, airport security, and others because of its unique characteristics for each person that cannot be replicated in another person. Therefore, most security systems rely and verify biometric properties. Airport security systems rely directly on facial recognition, but these systems may be exposed to attacks by the use of morphing faces in the passport image that allows multiple users to use the same passport. This paper presents a complete system consist of three stage, the first stage generating morphing faces based on edge detection to determine landmark and combine between landmarks to produce morphing. The second stage passing images on to the face recognition system that using Local Binary Pattern to features extraction, the final stage how to detect image bona fide or morph using texture techniques represented by each Local binary pattern and Gray-Level Co-Occurrence Matrix. With the use of the Wasserstein Distance measure, which has not previously been used in this field. The method gave effective results showing the mechanism of reducing morphing attack.

A parallel algorithm for finding the human face in the image

It is well-known that anyone who processes and analyzes image information needs a large amount of memory for storing images. For example, for storing a standard TV frame, if two of the three colors contain 2 bits for each of the 3 bits, the memory of at least 512×512 bytes is required. A passport image must be at least 64×64×64 bits (this requires more space than any other passport data). The problems associated with storage, search, and discovery are made more complex by processing and analyzing large numbers of images. The image contains a large amount of information, so it is natural for them to have excessive statistical, psychovisual and content information. Due to this redundancy, the process of digital image processing, image retrieval time, and storage capacity increase. The use of parallel technologies in digital processing of images plays an important role in solving the above problems. Therefore, the article presents an algorithm for calculating the process of extracting a human face from a color image using MPI technology.

A passport recognition and face verification using enhanced fuzzy ART based RBF network and PCA algorithm

In this paper, passport recognition and face verification methods which can automatically recognize passport codes and discriminate forgery passports to improve efficiency and systematic control of immigration management are proposed. Adjusting the slant is very important for recognition of characters and face verification since slanted passport images can bring various unwanted effects to the recognition of individual codes and faces. Therefore, after smearing the passport image, the longest extracted string of characters is selected. The angle adjustment can be conducted by using the slant of the straight and horizontal line that connects the center of thickness between left and right parts of the string. Extracting passport codes is done by Sobel operator, horizontal smearing, and 8-neighborhood contour tracking algorithm. The string of codes can be transformed into binary format by applying repeating binary method to the area of the extracted passport code strings. The proposed radial basis function (RBF) network is applied to the middle layer of RBF network by using the fuzzy logic connection operator and proposing the enhanced fuzzy adaptive resonance theory (ART) algorithm that dynamically controls the vigilance parameter. After several tests using a forged passport and the passport with slanted images, the proposed method was proven to be effective in recognizing passport codes and verifying facial images.

Intelligent Immigration Control System by Using Passport Recognition and Face Verification

This paper proposes the intelligent immigration control system that authorizes the traveler through immigration and detects forged passports by using automatic recognition of passport codes, the passport photo and face verification. The proposed system extracts and deskewes the areas of passport codes from the passport image. This paper proposes the novel ART algorithm creating the adaptive clusters to the variations of input patterns and it is applied to the extracted code areas for the code recognition. After compensating heuristically the recognition result, the detection of forged passports is achieved by using the picture and face verification between the passport photo extracted from the passport image and the picture retrieved from the database based on the recognized codes. Due to the proposed ART algorithm and the heuristic refinement, the proposed system relatively shows better performance.

Passport Recognition using Fuzzy Binarization and Enhanced Fuzzy RBF Network

Today, an automatic and accurate processing using computer is essential because of the rapid increase of travelers. The determination of forged passports plays an important role in the immigration control system. Hence, as the preprocessing phase for the determination of forged passports, this paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.