Abstract
Abstract Vision-based surface coverage measurement serves a large area of applications including robotic shot peening, robotic inspection in the fields of blood cell segmentation, coin recognition systems and many more. Manual visual inspection is time consuming and prone to human error. The objective is to develop a real-time generic algorithm, robust to non-uniform illumination with high accuracy, and having a relatively simple experimental setup. In this paper, a hybrid method based on morphological operations and Boykov graph-cuts segmentation is proposed for vision-based surface coverage measurement. The primary focus is on shot peening; however, the proposed algorithm will be extended towards other applications such as blood cell segmentation and coin recognition. The performance of the proposed algorithm is evaluated experimentally.
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