The Tropical Rainfall Measuring Mission (TRMM) satellite has collected a plenty of radiances from global clouds and precipitation, providing invaluable datasets for parameter retrieval of clouds and precipitation, in which cloud detection undoubtedly plays a key role. A cloud detection scheme, available during daytime, was proposed relying on five-channel measurements from TRMM visible and infrared scanner (VIRS). Three kinds of pixels including clear-sky, mixed-cloudy and cloudy ones are separated by such a scheme, which contains three major steps, i.e., terrain recognition, two-dimensional table search and decision tree determination. A comparison was conducted specially with MODIS standard cloud products to verify the cloud detection. It was demonstrated that the accuracy of cloud detection is satisfied on the whole, especially for grounds that are not covered by snow and ice, with mean cloud fraction bias less than 5%. When applied to cases companied by snow and ice in winter and or over plateau area, the 1.6 m channel reflectivity information, combined with 3.7 m and 10.8 m channel BT, were used to identify snow and ice covered sky in this cloud detection scheme, which made snow-covered sky pixels and cloud pixels well separated. Therefore, the proposed cloud detection scheme can be used to TRMM VIRS with considerable reliance, which leads to great convenience for further application of associated TRMM multiple-sensor measurements.