Worked on the danforthcenter/plantcv repository to enhance the reliability of the circle-detection workflow used in automated image analysis. Focused on improving error handling by introducing a robust failure path for Hough Circle Detection, ensuring the process terminates gracefully with an informative message when no circles are found. Updated supporting helper functions to align with the new error handling logic, reducing silent failures and preventing downstream pipeline crashes. Employed Python and Pytest to implement and verify these changes, emphasizing defensive programming and unit testing. The work improved user feedback and contributed to more stable research pipelines for image processing tasks.