The present invention discloses a part identification and positioning method based on a mixed model, belonging to the field of image processing technology. The method comprises the steps of: S1, collecting part images, identifying parts in the part images by employing a template matching algorithm, and obtaining one pose corresponding to each part; S2, extracting one edge point set of each identified part, and extracting an edge point set of a template image and a direction vector thereof; S3, based on a Gaussian mixture model, constructing one likelihood function of geometrical errors betweeneach part edge point set and the edge point set of the template image; S4, employing an EM algorithm to perform optimization of the constructed likelihood functions, and obtaining optimal values of the geometrical errors; and S5, employing the optimal values of the geometrical errors to perform correction of the poses of the corresponding parts, obtaining one corrected pose of each part, and identifying each part in the part images. The part identification and positioning method based on the mixed model has accurate identification and positioning effects and has good robustness.