To address the demand for high-precision machine vision measurement of the relatively large-sized parts, monocular telecentric systems suffer from a limited measurement range, while parallel telecentric systems risk lens interference. This paper therefore proposes an orthogonal telecentric machine vision measurement method and system. Firstly, the orthogonal telecentric system is established, with a detailed explanation of its composition principle and workflow. Subsequently, the calibration method for this system is investigated, introducing a mirror coordinate transformation model into the monocular telecentric imaging model and unifying the coordinate systems of the two non-overlapping-field-of-view telecentric systems using a calibration artifact. Next, key algorithms for the system are studied, including image quality evaluation based on multi adjacent pixel gradients, two-step corner localization based on image gradient information and coordinate linear optimization, sub-pixel edge detection, and automatic measurement point recognition and localization based on skeleton extraction and depth first search strategy. Finally, experimental studies and a comprehensive error model are employed to verify the system′s measurement accuracy and analyze key influencing factors. Experimental results show that the absolute error does not exceed 0.012 mm when measuring Grade 0 gauge blocks. For glass mold bottleneck dimension measurements, the maximum absolute error, minimum absolute error, and root mean square error (RMSE) are 0.035, 0.002, and 0.014 mm, respectively. The proposed orthogonal telecentric system demonstrates high measurement accuracy and consistency, enabling high-precision measurement of the relatively large-sized parts.