State-of-the-art　reservoir　computing　(RC)　systems　rely　on　preprocessed　images　as　the　input　layer＇s　signal　source,　lacking　the　capacity　to　directly　identify　physical　targets.　In　this　study,　we　develop　a　near-infrared　sensor　RC　system　tailored　for　direct　physical　target　detection.　This　system　integrates　a　lead　sulfide　quantum　dots　(PbS　QDs)based　near-infrared　sensor　array,　zinc　oxide　(ZnO)-based　memristors,　and　peripheral　circuits.　The　PbS　QDs　sensor　array　serves　as　the　signal　source　of　the　input　layer　of　the　RC　system,　capturing　image　information　through　nearinfrared　light　and　converting　it　into　a　temporal　signal　that　is　input　into　a　reservoir　composed　of　ZnO　memristors.　Memristors　exhibit　robust　resistance　switching　stability　and　synaptic　characteristics,　enabling　superior　reservoir　state　separation　within　RC　systems.　The　results　demonstrate　that　the　recognition　accuracy　for　5　x　4　digital　images　exceeds　88　%.　This　system　provides　a　promising　way　for　the　future　development　of　intelligent　infrared　cameras　and　shows　its　potential　in　complex　target　recognition.