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　near-infrared　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　×　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.　©　2025　Elsevier　B.V.