The primary objective of this research paper is to detect and quantify the necking defect and surface velocity profiles in high-speed polymer melt extrusion film casting (EFC) process using Matlab® based image processing techniques. Extrusion film casting is an industrially important manufacturing process and is used on an industrial scale to produce thousands of kilograms of polymer films/sheets and coated products. In this research, the necking defect in an EFC process has been studied experimentally and the effects of macromolecular architecture such as long chain branching (LCB) on the extent of necking have been determined using image processing methodology. The methodology is based on the analysis of a sequence of image frames taken with the help of a commercial CCD camera over a specific target area of the EFC process. The image sequence is then analyzed using Matlab® based image processing toolbox wherein a customized algorithm is written and executed to determine the edges of the extruded molten polymeric film to quantify the necking defect. Alongwith the necking defect, particle tracking velocimetry (PTV) technique is also used in conjunction with the Matlab® software to determine the centerline and transverse velocity profiles in the extruded molten film. It is concluded from this study that image processing techniques provide valuable insights into quantifying both the necking defect and the associated velocity profiles in the molten extruded film. © 2021 Kingfa SCI. & TECH. CO., LTD.