Muscle imaging is a promising field of research to understand the biological and bioelectrical characteristics of muscles through the observation of muscle architectural change. Sonomyography (SMG) is a technique which can quantify the real-time architectural change of muscles under different contractions and motions with ultrasound imaging. The pennation angle and fascicle length are two crucial SMG parameters to understand the contraction mechanics at muscle level, but they have to be manually detected on ultrasound images frame by frame. In this study, we proposed an automatic method to quantitatively identify pennation angle and fascicle length of gastrocnemius (GM) muscle based on multi-resolution analysis and line feature extraction, which could overcome the limitations of tedious and time-consuming manual measurement. The method started with convolving Gabor wavelet specially designed for enhancing the line-like structure detection in GM ultrasound image. The resulting image was then used to detect the fascicles and aponeuroses for calculating the pennation angle and fascicle length with the consideration of their distribution in ultrasound image. The performance of this method was tested on computer simulated images and experimental images in vivo obtained from normal subjects. Tests on synthetic images showed that the method could identify the fascicle orientation with an average error less than 0.1°. The result of in vivo experiment showed a good agreement between the results obtained by the automatic and the manual measurements (r=0.94±0.03; p<0.001, and r=0.95±0.02, p<0.001). Furthermore, a significant correlation between the ankle angle and pennation angle (r=0.89±0.05; p<0.001) and fascicle length (r=-0.90±0.04; p<0.001) was found for the ankle plantar flexion. This study demonstrated that the proposed method was able to automatically measure the pennation angle and fascicle length of GM ultrasound images, which made it feasible to investigate muscle-level mechanics more comprehensively in vivo.