Traditional　approaches　to　environmental　sounds　recognition　used　acoustic　features　merely　based　on　time　domain　or　frequency　domain.　In　this　paper,　a　new　feature　descriptor　that　uses　image　texture　information　is　proposed　to　identify　specific　environmental　sounds　based　on　the　recognition　of　fixed-duration　sounds　segments　where　their　corresponding　spectrums　are　viewed　as　gray-level　images.　The　proposed　specific　environmental　sounds　recognition　system　firstly　conducts　short-time　spectrum　estimation　algorithm　to　the　noisy　sounds　segments,　and　then　extracts　5　time-frequency　texture　features　descriptors(TFD)　from　the　enhanced　spectrum　using　sum　and　difference　histogram　(SDH),　in　the　last　place,　applies　random　forest(RF)　to　make　classification　and　recognition.　The　average　recognition　rate　is　92.5%　for　51　kinds　of　environmental　sounds,　outperforming　the　well-known　MFCC　features;　meanwhile,　it　is　robust　to　noise.