Effective Computer Model For Recognizing Nationality From Frontal Image
This addresses a specific biometric identification problem for security and institutional applications, but appears incremental with no performance metrics provided.
The paper tackles nationality recognition from frontal face images by analyzing face part colors, sizes, and distances, with the model applicable in military, police, defense, healthcare, and technology sectors.
We are introducing new effective computer model for extracting nationality from frontal image candidate using face part color, size and distances based on deep research. Determining face part size, color, and distances is depending on a variety of factors including image quality, lighting condition, rotation angle, occlusion and facial emotion. Therefore, first we need to detect a face on the image then convert an image into the real input. After that, we can determine image candidate gender, face shape, key points and face parts. Finally, we will return the result, based on the comparison of sizes and distances with the sample measurement table database. While we were measuring samples, there were big differences between images by their gender and face shapes. Input images must be the frontal face image that has smooth lighting and does not have any rotation angle. The model can be used in military, police, defense, healthcare, and technology sectors. Finally, Computer can distinguish nationality from the face image.