Computer Vision Assisted Orientation Estimation
This paper is intended to solve the object orientation problem that arises during the object recognition phase of production testing. Analysis is done on three algorithms: Radon Transform, Hough Transform, andFeature Extraction utilizing Speeded Up Robust Feature (SURF). After evaluating the outcomes of three approaches, the drawbacks are examined. Optical Character Recognition (OCR) requirements mean that, despite Radon transform and Hough transform requiring fewer computational steps, they cause higher error and require more processing time. Meanwhile, SURF produces significantly less error, is faster and more efficient.
Keywords - Speeded Up Robust Features, Orientation Estimation, Radon, Hough, Feature Extraction.