The traditional polarization-maintaining fiber alignment method is divided into longitudinal and lateral observation methods. However, both of them have severe defects. For example, the longitudinal observation method limits the application scenarios due to the destruction of the polarization fiber in the detection section. In contrast, the widely used lateral observation method requires high standards for experimental equipment and complex manual operations and alignment algorithms. Regarding the panda polarization maintaining fiber as the research object, instead of the traditional polarization-maintaining fiber alignment thinking of applying a high standard light source and adjusting the imaging surface. Based on applying the matching liquid mixed with glycerin and deionized water, the ideal refraction environment can be created due to the reduced effects of multiple spherical aberrations. Hence, high accuracy visualization can be achieved by projection from the incoherent parallel light sources. Then, applying the rotating motor with a fiber clamp setup and imaging system to form an experimental device, a long-distance section of the polarization-maintaining fiber can be aligned. Additionally, the LabVIEW platform can demonstrate the results of direct observation and real-time extraction of light intensity distribution information, which contains angle information of the polarization axis from the polarization-maintaining fiber. This information can also be called the characteristic value of the high accuracy alignment method, i.e., the three segment diffraction fringe spaces $d_{\mathrm{2}}$, $d_{\mathrm{3}}$, $d_{\mathrm{4}}$, which are sensitive to the polarization axis angle θ inside the polarization-maintaining fiber. According to the internal structure of the polarization-maintaining fiber and the geometric characteristics of the eigenvalue, the geometric relationship between the eigenvalue and the angle of the polarization axis θ of the polarization-maintaining fiber can be deduced theoretically. Furthermore, through computer processing of the experimental data and theoretical analysis of the light intensity distribution, the relationship between the characteristic areas and the angle of the polarization axis was obtained. Thus, real-time alignment between the polarization axis of the polarization fiber and the observation surface could be realized. In the case of the image processing algorithm, the collected information is primarily binarized and converted into gray-scale digital signals, and then the collected data are normalized to improve the signal-to-noise ratio and reconstruct the image edge by the two-dimensional wavelet algorithm. Due to these algorithm techniques, the accuracy of the alignment method has been improved significantly, the deviation ratio is better than 1.32%, and the accuracy of the alignment method is up to $\pm \mathrm{0.3}°$. Moreover, polarization-maintaining fibers might have several process defects, and the primary influencing factors are material purity and environmental impacts during the drawing manufacturing process. All of these defects lead to three typical asymmetries of the panda eyes distribution: the radii of the two panda eyes are inconsistent, the distance between the center of the two panda eyes is inconsistent, and the line of the center of the two panda eyes is not collinear with the line of the center of the fiber core. According to the analysis of geometric theory, the high-precision positioning method is also compatible with the errors caused by the asymmetry of the panda eyes distribution.