In recent years, morbidity and mortality of the cardiovascular or cerebrovascular disease, which threaten human health greatly, increased year by year. Heart rate is an important index of these diseases. To address this status, the paper puts forward a kind of simple structure, easy operation, suitable for large populations of daily monitoring non-contact heart rate measurement. In the method we use imaging equipment video sensitive areas. The changes of light intensity reflected through the image grayscale average. The light change is caused by changes in blood volume. We video the people face which include the sensitive areas (ROI), and use high-speed processing circuit to save the video as AVI format into memory. After processing the whole video of a period of time, we draw curve of each color channel with frame number as horizontal axis. Then get heart rate from the curve. We use independent component analysis (ICA) to restrain noise of sports interference, realized the accurate extraction of heart rate signal under the motion state. We design an algorithm, based on high-speed processing circuit, for face recognition and tracking to automatically get face region. We do grayscale average processing to the recognized image, get RGB three grayscale curves, and extract a clearer pulse wave curves through independent component analysis, and then we get the heart rate under the motion state. At last, by means of compare our system with Fingertip Pulse Oximeter, result show the system can realize a more accurate measurement, the error is less than 3 pats per minute.