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Recently, quaternion collaborative representation-based classification (QCRC)and quaternion sparse representation-based classification (QSRC) have beenproposed for color face recognition. They can obtain correlation informationamong different color channels. However, their performance is unstable indifferent conditions. For example, QSRC performs better than than QCRC on somesituations but worse on other situations. To benefit from quaternion-based$e_2$-norm minimization in QCRC and quaternion-based $e_1$-norm minimization inQSRC, we propose the quaternion-based adaptive representation (QAR) that uses aquaternion-based $e_p$-norm minimization ($1 \le p \le 2$) for color facerecognition. To obtain the high dimension correlation information amongdifferent color channels, we further propose the high-dimensionquaternion-based adaptive representation (HD-QAR). The experimental resultsdemonstrate that the proposed QAR and HD-QAR achieve better recognition ratesthan QCRC, QSRC and several state-of-the-art methods.

Color Face Recognition using High-Dimension Quaternion-based Adaptive Representation