One of the most common approaches to address the partial face recognition
challenge is to crop the full face image into segments. The problem is how
the full face image must be cropped in a uniform way to generate informative
segments. The un-blindly strategy was applied in this paper to generate
informative segments, it depends on localizing the facial landmarks and
selecting the more informative facial points as a key points, as more as the knearest
neighbor concept was explored to select the k nearest landmark
points to the key points. Two landmark localization techniques were
experimented, the suitable technique resulted in segments which are
overlapped due to the supervised clustering technique that explored in this
paper to cover important biometric face regions, not repeated and covered
most probabilities in which it is possible to distinguish the query face from
the available part of it.
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