Variations　in　lighting　conditions　make　face　recognition　an　even　more　challenging　and　difficult　task.　In　this　paper,　a　novel　approach　is　proposed　to　handle　the　illumination　problem.　Our　method　can　restore　a　face　image　captured　under　arbitrary　lighting　conditions　to　one　with　frontal　illumination　by　using　a　ratio-image　and　an　iterative　algorithm.　The　restored　images　with　frontal　illumination　are　used　for　face　recognition　by　means　of　PCA.　Experimental　results　demonstrate　that　our　method　can　achieve　a　higher　recognition　rate　based　on　the　Yale　B　and　Yale　database.　Moreover,　our　algorithm　has　several　advantages　over　other　previous　algorithms:　(1)　does　not　need　to　estimate　the　face　surface　normals　and　the　light　source　directions,　(2)　it　does　not　need　many　images　captured　under　different　lighting　conditions　for　each　person,　nor　a　set　of　bootstrap　images　that　includes　many　images　with　different　illuminations,　and　(3)　it　does　not　need　to　detect　accurate　positions　of　some　facial　feature　points　and　to　warp　image　for　alignment,　etc.