In order to easily and effectively identify HCM and normal heart sound, this paper proposed a new method based on timefrequency domain (TFD) feature extraction algorithm of heart murmur for HCM heart sound. Wavelet transform and principle component analysis were applied to preprocessing. The time domain envelope of the signal based on frequency conversion homomorphic filtering (FCHF) was extracted. The segmentation and localization were performed to extract the systolic energy Es and diastolic murmur energy Ed. The heart murmur scaling factor (SF) was extracted by power spectral estimation. The SF was used to weight Es and Ed, gaining the quantitative indicators for representing heart murmurs. 100 normal heart sound and 181 HCM heart sound were classified for verifying the validity of quantitative indicators. The accuracy on average was 92.97%, the best performance was 95.37%. Result represented that the extracted features can effectively classify normal heart sound and HCM heart sound. The algorithm extracted quantitative indicators of representing heart murmurs can effectively represent heart murmur. The proposed algorithm is used to provide technical basis for classification and recognition of HCM heart sounds.