In the metal forming processes, the sheet metals are often prone to various defects such as thinning, dents, wrinkles etc. In the present manufacturing environments with ever increasing demand of higher quality, detecting the defects of formed sheet metal using an effective and objective inspection system is the foremost norm to remain competitive in market. The defect detection using optical techniques aspire to satisfy its needs to be non-contact and fast. However, the main difficulties to achieve this goal remain essentially on the development of efficient evaluation technique and accurate interpretation of extracted data. The defect like thinning is detected by evaluating the deviations of the thickness in the
formed sheet metal against its nominal value. The present evaluation procedure for determination of thickness applied on the measurements data is not without deficiency. To improve this procedure, a new evaluation approach based on medial axis transformation is proposed here. The formed sheet metals are digitized using fringe projection systems in different orientations, and afterwards registered into one coordinate frame. The medial axis transformation (MAT) is applied on the point clouds, generating the point clouds of MAT. This data is further processed and medial surface is determined. The thinning defect is detected by evaluating local wall thickness and other defects like wrinkles are determined using the shape recognition on the medial surface. The applied algorithm is simple, fast and robust.