Survey on Different Morphology Detection Techniques (original) (raw)
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Detecting Morphing Attacks through Face Geometry Features
Journal of Imaging
Face-morphing operations allow for the generation of digital faces that simultaneously carry the characteristics of two different subjects. It has been demonstrated that morphed faces strongly challenge face-verification systems, as they typically match two different identities. This poses serious security issues in machine-assisted border control applications and calls for techniques to automatically detect whether morphing operations have been previously applied on passport photos. While many proposed approaches analyze the suspect passport photo only, our work operates in a differential scenario, i.e., when the passport photo is analyzed in conjunction with the probe image of the subject acquired at border control to verify that they correspond to the same identity. To this purpose, in this study, we analyze the locations of biologically meaningful facial landmarks identified in the two images, with the goal of capturing inconsistencies in the facial geometry introduced by the mo...
Morphing Attack Detection - Database, Evaluation Platform and Benchmarking
IEEE Transactions on Information Forensics and Security
Morphing attacks have posed a severe threat to Face Recognition System (FRS). Despite the number of advancements reported in recent works, we note serious open issues such as independent benchmarking, generalizability challenges and considerations to age, gender, ethnicity that are inadequately addressed. Morphing Attack Detection (MAD) algorithms often are prone to generalization challenges as they are database dependent. The existing databases, mostly of semi-public nature, lack in diversity in terms of ethnicity, various morphing process and post-processing pipelines. Further, they do not reflect a realistic operational scenario for Automated Border Control (ABC) and do not provide a basis to test MAD on unseen data, in order to benchmark the robustness of algorithms. In this work, we present a new sequestered dataset for facilitating the advancements of MAD where the algorithms can be tested on unseen data in an effort to better generalize. The newly constructed dataset consists of facial images from 150 subjects from various ethnicities, age-groups and both genders. In order to challenge the existing MAD algorithms, the morphed images are with careful subject pre-selection created from the contributing images, and further post-processed to remove morphing artifacts. The images are also printed and scanned to remove all digital cues and to simulate a realistic challenge for MAD algorithms. Further, we present a new online evaluation platform to test algorithms on sequestered data. With the platform we can benchmark the morph detection performance and study the generalization ability. This work also presents a detailed analysis on various subsets of sequestered data and outlines open challenges for future directions in MAD research.
Morph Creation and Vulnerability of Face Recognition Systems to Morphing
Advances in computer vision and pattern recognition, 2022
Face recognition in controlled environments is nowadays considered rather reliable, and very good accuracy levels can be achieved by state-of-the-art systems in controlled scenarios. However, even under these desirable conditions, digital image alterations can severely affect the recognition performance. In particular, several studies show that automatic face recognition systems are very sensitive to the so-called face morphing attack, where face images of two individuals are mixed to produce a new face image containing facial features of both subjects. Face morphing represents nowadays a big security threat particularly in the context of electronic identity documents because it can be successfully exploited for criminal intents, for instance to fool Automated Border Control (ABC) systems thus overcoming security controls at the borders. This chapter will describe the face morphing process, in an overview ranging from the traditional techniques based on geometry warping and texture blending to the most recent and innovative approaches based on deep neural networks. Moreover, the sensitivity of state-of-the-art face recognition algorithms to the face morphing attack will be assessed using morphed images of different quality generated using various morphing methods to identify possible factors influencing the probability of success of the attack.
Generating and Detecting Face Morphing Using Texture Techniques
Journal of Kufa for Mathematics and Computer
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-O...
Electronic Imaging
In recent years, ID controllers have observed an increase in the use of fraudulently obtained ID documents [1]. This often involves deception during the application process to get a genuine document with a manipulated passport photo. One of the methods used by fraudsters is the presentation of a morphed facial image. Face morphing is used to assign multiple identities to a biometric passport photo. It is possible to modify the photo so that two or more persons, usually the known applicant and one or more unknown companions, can use the passport to pass through a border control [2]. In this way, persons prohibited from crossing a border can cross it unnoticed using a face morphing attack and thus acquire a different identity. The face morphing attack aims to weaken the application for an identity card and issue a genuine identity document with a morphed facial image. A survey among experts at the Security Printers Conference revealed that a relevant number of at least 1,000 passports with morphed facial images had been detected in the last five years in Germany alone [1]. Furthermore, there are indications of a high number of unreported cases. This high presumed number of unreported cases can also be explained by the lack of morphed photographs' detection capabilities. Such identity cards would be recognized if the controllers could recognize the morphed facial images. Various studies have shown that the human eye has a minimal ability to recognize morphed faces as such [2], [3], [4], [5], [6]. This work consists of two parts. Both parts are based on the complete development of a training course for passport control officers to detect morphed facial images. Part one contains the conception and the first test trials of how the training course has to be structured to achieve the desired goals and thus improve the detection of morphed facial images for passport inspectors [7]. The second part of this thesis includes the training course and the evaluation of its effectiveness.
PRNU-Baseddetection of Morphed Face Images
Recently, researchers found that the intended generalizability of face recognition systems increases their vulnerability against attacks. In particular, the attacks based on morphed face images pose a severe security risk to face recognition systems. In the last few years, the topic of (face) image morphing and automated morphing attack detection has sparked the interest of several research laboratories working in the field of biometrics and many different approaches have been published. In this paper, a morphing attack detection system based on the analysis of "Photo Response Non Uniformity" (PRNU) is presented. More specifically, spatial and spectral features extracted from PRNU patterns across image cells are analysed and also analyses DFT plot for spatial features and absolute DFT for spectral features. This PRNU can be extracted by using DWT. Differences of these features for bona fide and morphed images are estimated during a threshold-selection at last. The proposed PRNU-based morphing attack detector is shown to robustly distinguish bona fide and morphed face images.
On the vulnerability of face recognition systems towards morphed face attacks
2017 5th International Workshop on Biometrics and Forensics (IWBF), 2017
Morphed face images are artificially generated images, which blend the facial images of two or more different data subjects into one. The resulting morphed image resembles the constituent faces, both in visual and feature representation. If a morphed image is enroled as a probe in a biometric system, the data subjects contributing to the morphed image will be verified against the enroled probe. As a result of this infiltration, which is referred to as morphed face attack, the unambiguous assignment of data subjects is not warranted, i.e. the unique link between subject and probe is annulled. In this work, we investigate the vulnerability of biometric systems to such morphed face attacks by evaluating the techniques proposed to detect morphed face images. We create two new databases by printing and scanning digitally morphed images using two different types of scanners, a photo scanner and a line scanner. Further, the newly created databases are employed to study the vulnerability of state-of-the-art face recognition systems with a comprehensive evaluation.
Techniques and Challenges for Generation and Detection Face Morphing Attacks: A Survey
Iraqi journal of science, 2023
Face recognition system is the most widely used application in the field of security and especially in border control. This system may be exposed to direct or indirect attacks through the use of face morphing attacks (FMAs). Face morphing attacks is the process of producing a passport photo resulting from a mixture of two images, one of which is for an ordinary person and the other is a judicially required. In this case, a face recognition system may allow travel of persons not permitted to travel through face morphing image in a Machine-Readable Electronic Travel Document (eMRTD) or electronic passport at Automatic Border Control (ABC) gates. In creating an electronic passport, most countries rely on applicant to submit images in a form of a document or via the Internet, and this allows applicants to manipulate the images to produce morphing images. These photos allow both beneficial and harmful partners to cross borders using the same passport. This is considered a major threat to the security systems that allow them to travel without revealing their true identity. This paper aims to provide a comprehensive overview of face morphing attacks and the development taking place in this specialty. This paper describes the techniques for generating metamorphic images and challenges they face, in addition to the advantages and disadvantages of these techniques. It also dealt with types of techniques used in detecting and determining the attack of mutant faces in the field of deep learning or machine learning, in addition to the laws and criteria for measuring the efficiency of the algorithms used. It provides a general summary of the work that has been produced in this field.
ANALYSIS OF DIGITAL IMAGES USING MORPHLOGICAL OPERATIONS
The main aim of this study is to transform the digital images into different forms. Image processing techniques are used with wide varieties of applications. The requirement is different for different applications. This study is mainly focused on how to transform the image using mathematical morphology so that it can be suitable for the respective applications. Mathematical morphology has been chosen to explain how images are used to illustrate mathematical set theoretic operations, such as union, intersection by means of morphological operations like dilation and erosion. These techniques are implemented in MATLAB using image processing algorithms. MATLAB is an excellent tool to accomplish these tasks.
2019
Since the face morphing attack was introduced by Ferrara et al. in 2014, the detection of face morphings has become a wide spread topic in image forensics. By now, the community is very active and has reported diverse detection approaches. So far, the evaluations are mostly performed on images without post-processing. Face images stored within electronic machine readable documents (eMRTD) are ICAO-passport-scaled to a resolution of 413x531 and a JPG or JP2 lesize of 15 kilobytes. This paper introduces a face morphing detection concept with 3 modules (ICAO-aligned pre- processing module, feature extraction module and classi cation module), tailored for such images on eMRTD. In this work we exemplary design and evaluate two feature spaces for the feature extraction module, a frequency domain and a spatial domain feature space. Our evaluation will compare both feature spaces and is carried out with 66,229 passport-scaled images (64,363 morphed face images and 1,866 authentic face image...