Illumination invariant single face image recognition under heterogeneous lighting condition

作者：

Highlights：

• Two illumination invariant components, namely logarithm gradient orientation (LGO) and logarithm gradient magnitude (LGM), are extracted.

• An effective post-processing strategy is proposed to integrate both LGO and LGM, generating the logarithm gradient histogram (LGH).

• Solid theoretical analysis on the illumination invariant properties of the proposed descriptors is presented.

• Competitive results are reported, both in homogeneous and heterogeneous lighting conditions.

摘要

Highlights•Two illumination invariant components, namely logarithm gradient orientation (LGO) and logarithm gradient magnitude (LGM), are extracted.•An effective post-processing strategy is proposed to integrate both LGO and LGM, generating the logarithm gradient histogram (LGH).•Solid theoretical analysis on the illumination invariant properties of the proposed descriptors is presented.•Competitive results are reported, both in homogeneous and heterogeneous lighting conditions.

论文关键词：Face recognition,Illumination invariant feature,Heterogeneous lighting,Gradient histogram

论文评审过程：Received 23 February 2016, Revised 22 September 2016, Accepted 31 December 2016, Available online 3 January 2017, Version of Record 12 March 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.12.029