Face recognition using special neural networks

Kussul, Ernst; Baydyk, Tetyana

doi:10.1109/ijcnn.2015.7280401

Cited by 6 publications

(1 citation statement)

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“…The differential morph detection method has been used extensively in the literature by utilizing different techniques of feature extraction and comparison [1,[20][21][22][23][24][25]. In [5], a robust differential morphing attack detection model was presented that efficiently classified morphed images generated from four different morphing tools.…”

Section: Feature Extraction and Comparisonmentioning

confidence: 99%

A Comprehensive Review of Face Morph Generation and Detection of Fraudulent Identities

et al. 2022

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A robust facial recognition system that has soundness and completeness is essential for authorized control access to lawful resources. Due to the availability of modern image manipulation technology, the current facial recognition systems are vulnerable to different biometric attacks. Image morphing attack is one of these attacks. This paper compares and analyzes state-of-the-art morphing attack detection (MAD) methods. The performance of different MAD methods is also compared on a wide range of source image databases. Moreover, it also describes the morph image generation techniques along with the limitations, strengths, and drawbacks of each morphing technique. Results are investigated and compared with in-depth analysis providing insight into the vulnerabilities of existing systems. This paper provides vital information that is essential for building a next generation morph attack detection system.

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