Three wheelers (3Ws) are widely used in low and middle-income countries, particularly in Asia Pacific region as a comparatively cheap method to passenger transportation and goods delivery. The frequent use of 3Ws in day-to-day activities have caused a large number of accidents causing injuries to their passengers. Less research has been carried out to identify the reasons behind 3W accidents. The survey carried out prior to this research has identified that the stability control and speed control are the two key factors which the 3W accidents attributed to. 3W fork is the main mechanical element that controls the balance and the stability of the vehicle. A damaged 3W fork (a physical damage or a slight deformation) unbalances the 3W and had been identified as one of the reasons for large number of accidents. Therefore, correctly reforming the damaged fork is of paramount importance, when concerning the safety of the 3Ws. Traditionally, both heat-treating and cold-working techniques are used in the mending processes. Not only this manual-labor repairing process weakens the strength of the fork, but also the profile produced is inaccurate. This paper discusses a hydraulic operated fork mending machine with an image processing technique to reform the damaged forks in 3Ws. An image comparator-based imaging technique is used for this machine vision-based visually guided fork repairing process. Three cameras have been used to capture the images from three perpendicular directions. A contour sketch of the original fork (before the deformation occurs) has been compared against the faulty fork, to assist the worker to carry out the repairing process. The preliminary experimentations have shown that the proposed technique can improve the repositioning of the camber angle by repairing the damaged fork.