A Generating and Detecting Face Morphing Using Texture Techniques

Generating and Detecting Face Morphing Using Texture Techniques


  • iman saleem University kufa
  • Bahja Khudair Shukr University of Kufa




Edge Detection , Face recognition, Wasserstein Distance, Face landmark, Local Binary Pattern, Gray-Level Co-Occurrence Matrix.


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. 


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How to Cite

saleem, iman, & Shukr, B. K. (2023). A Generating and Detecting Face Morphing Using Texture Techniques: Generating and Detecting Face Morphing Using Texture Techniques. Journal of Kufa for Mathematics and Computer, 10(1), 102–107. https://doi.org/10.31642/JoKMC/2018/100115

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