Aiming to the quality control and service performance evaluation of metal plate, a dynamic time warping of guided waves method based on shape context is proposed to quantify the micro-damage in aluminum plate. Using the Lamb wave signal of intact metal plate as the baseline, the dynamic time warping (DWT) algorithm is applied to match the damage Lamb wave signal to the baseline so as to determine the optimal warping path. The shape context (SC) contour recognition method is introduced to statistically analyze the local waveform information of Lamb waves. The shape distance of waveform is used to replace the Euclidean distance of traditional DTW, and the ill alignment problem in the Lamb signal similarity matching is solved. Finally, the SC-DTW matching distance between damaged signal and baseline is used as a quantitative index to describe the damage degree of aluminum plate. The finite element simulation model of random closed crack and bending test of aluminum plate are used to verify the proposed method. The results show that the proposed SC-DTW method has high sensitivity and noise robustness for early crack damage detection of aluminum plate, and the proposed damage index has a good linear correlation with the fatigue damage degree of aluminum plate. This method does not need to identify the damage wave packet, and does not need to deal with the feature extraction. It has the advantages of simplicity, high efficiency and strong anti-noise ability. It has good practicability and popularization value in the quality control and service performance evaluation of metal plates.