This paper presents a vocal themes extraction algorithm based on multi-candidate fundamental frequency extraction and singing voice fundamental frequency discrimination. The algorithm can effectively reduce the voicing false alarm rate and improve the overall accuracy. First, using the Distance(DIS) metric distance algorithm to achieve note segmentation, and using the variance method to detect voiced segments. Then Pitch Estimation Filter with Amplitude Compression(PEFAC) multi- fundamental frequency extraction technology is utilized to extract multiple candidate fundamental frequencies of each voiced frame by calculating the pitch saliency. Finally, the dominant fundamental frequency trajectory of the voiced segment is tracked by the Viterbi algorithm, and the main melody of the singing voice is determined by the fundamental frequency discrimination model. Experiments conducted on the MIR-1K dataset show that the overall accuracies of the vocal themes extracted by the proposed algorithm reach 86.22% and 77.4%, respectively, at the signal to interference ratio of 5 dB and 0 dB, which are increased by at least 3.79% and 2.01% respectively compared to other algorithms.