Sparse　representation　based　classification　(SRC)　has　gained　great　success　in　image　recognition.　In　this　paper,　we　propose　a　generalized　CRC　method,　essentially　a　SRC　using　Euler　sparse　representation,　for　image　classification.　To　be　specific,　our　CRC　first　maps　the　image　into　a　complex　space　by　Euler　representation　with　a　negligible　effect　for　outliers　and　illumination,　and　then　performs　a　complex　SRC　method.　We　also　present　a　fast　and　efficient　algorithm　to　solve　Euler　SRC　subproblems.　Extensive　experimental　results　illustrate　that　our　method　outperforms　traditional　SRC　methods　and　achieves　better　performance　for　image　classification.　©　2019　IEEE.