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The first-ever case of face morphing was reported by German federal police in 2013. An imposter forged a British e-passport to bypass border control security and gain illegitimate access to the system. In a world where technological development has streamlined many aspects of our lives, at the same time technology is being exploited by malicious actors for illicit activities. Facial morphing was initially implemented to offer astonishing applications in media & entertainment, but these days it is used by cybercriminals to get unauthorized access to services or privileges. Let’s briefly navigate what is morphing, the common techniques used, how the technology works, and how to prevent the associated threats.
A Closer Look into Face Morphing
Morphing is an advanced technique, where two or more images from multiple or the same resource are warped into each other to form a new identity. The produced identity could be a whole new identity or a combination of the input data. Facial morphing, which is largely employed by cybercriminals to generate highly realistic deepfakes later used to conduct illegitimate activities.
AI Face Morphing is advanced digital image manipulation technology, potentially generating a new identity by blending images acquired from targeted individuals. Various advanced techniques like computer vision, artificial intelligence, machine learning models, 3D facial recognition, and image processing software are integrated to produce sharp and super-realistic identities.
The Science Behind AI Face Morphs: Common Techniques
AI Face Morphing impose serious threats to privacy and security of confidential information and even biometrics are spoofed to facilitate such nefarious activities. Imposters with unethical intentions are employing advanced technologies integrated with AI & machine learning tools to effectively accomplish illicit activities. Multiple sophisticated techniques are integrated into morphing technology to produce sharp and realistic outputs.
Linear Morphing Technique
Linear morphing is simple and seamless as compared to other complex morphing techniques. It is largely used in computer vision and animations to warp input images to form a targeted identity. In this technique, the key points of the input images are detected, required key points are matched for accurate extraction and warped into each other to produce simple yet effective outputs.
Mesh Morphing
Mesh morphing is also referred to as grid-based morphing and it integrates advanced technologies to generate highly realistic results. The facial images are divided into triangles or quadrangles having different grids, and the resembling elements are warped into each other to produce symmetrical facial images. The technique can effectively handle complex or complicated image manipulation and is ultra-flexible in producing targeted identities.
3D Facial Morphing
Better known as geometric morphing involves the deforming and blending of 3D objects or images to generate identities resembling the input data. This morphing technique results in extravagant transition when the 3D vertices of one image are warped into the 3D vertices of another image, blurring the boundary line between real and fake.
Quick Insights into Working Principle
AI Face Morphing appear realistic to the extent that the boundary line between real and fake identities is blurred, even modern authentication systems fail to recognize the difference. Generative adversarial networks (GANs) are deployed to generate highly- realistic facial images or presentation masks, circumventing biometric authentication solutions and getting access to services.
- Collection of face images of targeted individuals: Morphing isn’t even-tempered technology, imposters spend a lot of energy and effort to collect images of the targeted images employing nefarious approaches. Collecting images is the first step in this technique which undergoes various key steps to produce sharp outputs.
- Detecting facial features of the resourced images: This step includes separating the Face Morphing from the rest of the image for better results. It’s like detecting your friend’s face from a big frame for better recognition.
- Extracting required facial attributes and correspondence: Facial features including the shape of the nose, the distance between both eyes, the contour of the jawline, or the depth of the mouth are minutely analyzed and extracted as per requirements.
- Deforming images & warping: This includes deforming the resource images carefully while taking them into account. The pixels of the input Face Morphing are completely deformed and warped into each other, however, the overall geometry of the Face Morphing is retained to produce similar identities.
- Blending & Interpolation: Cross-dissolve morphing or alpha morphing techniques are deployed for accurate blending of the facial features and micro details like skin texture or even wrinkles are taken care of while blending the input information.
- Refinement of the newly generated identity & final output: A single cohesive identity is produced containing elements from both input images. The final images are refined to enhance the quality and make it appear super realistic.
Final Thoughts
Face Morphing technology initially developed for applications in media & entertainment is widely employed for malicious activities. It impacts the overall security of victim’s sensitive information and most of the time victims are unaware of the act that their identities are exploited to conduct illegitimate activities. It’s crucial to develop robust preventive measures and stay cautious to mitigate the looming threats of impersonation attacks.
