Automatic　License　Plate　Recognition　(ALPR)　systems　have　become　popular　application　areas　of　the　Internet　of　Things　(IoT).　A　typical　ALPR　system　always　needs　powerful　processors　such　as　Cortex-A7.　However,　most　known　system　for　Standard　Definition　(SD)　are　not　suitable　for　real-time　High　Definition　(HD)　image　processing　and　low　power　consuming　requirement　in　IoT.　A　HD　ALPR　accelerator　for　the　IoT　endpoint　System　on　Chip　(SoC)　is　proposed　in　this　paper　to　meet　the　needs　of　computations.　Based　on　the　programming　flexibility　of　IoT　endpoint　SoC,　it　can　switch　between　HD　and　SD　resolutions,　which　can　avoid　the　specific　resolution　switching　algorithm.　A　Field　Programmable　Gate　Array　(FPGA)　chip　is　transplanted　the　Cortex-M0　as　the　IoT　endpoint　SoC,　through　the　design　of　ALPR　accelerator　and　Cortex-M0,　data　communication　is　achieved　by　First-In,　First-Out　(FIFO)　with　AMBA　High-performance　Bus　(AHB)　interface.　Heterogeneous　implementation　of　ALPR　system　has　shown　that　this　HD　ALPR　algorithm　can　recognize　a　license　plate　in　12.5ms,　with　a　success　rate　of　95.5%.　The　system　utilizes　41,763　Look-Up-Tables　(LUTs)　without　special　FPGA　IP　core.　The　comparison　shows　that　the　system　proposed　in　this　paper　makes　performance　of　the　SoC　based　on　the　Cortex-M0　kernel　was　two　times　higher　than　the　Cortex-A72　SoC　and　39%　of　the　power　consumption　of　Zynq-7000　that　is　typical　heterogeneous　ALPR　platform.　©　The　Author(＇s).　This　is　an　open　access　article　distributed　under　the　terms　of　the　Creative　Commons　Attribution　License　(CC　BY　4.0),　which　permits　unrestricted　use,　distribution,　and　reproduction　in　any　medium,　provided　the　original　author　and　source　are　cited.