  In this paper a local pattern descriptor in high order derivative space is
proposed for face recognition. The proposed local directional gradient pattern
(LDGP) is a 1D local micropattern computed by encoding the relationships
between the higher order derivatives of the reference pixel in four distinct
directions. The proposed descriptor identifies the relationship between the
high order derivatives of the referenced pixel in four different directions to
compute the micropattern which corresponds to the local feature. Proposed
descriptor considerably reduces the length of the micropattern which
consequently reduces the extraction time and matching time while maintaining
the recognition rate. Results of the extensive experiments conducted on
benchmark databases AT&T, Extended Yale B and CMU-PIE show that the proposed
descriptor significantly reduces the extraction as well as matching time while
the recognition rate is almost similar to the existing state of the art
methods.
