This thesis describes a camera calibration technique and an algorithm of fiducial mark recognition for a SMT(Surface Mounting Technology) board inspection system. And also it describes an implementation of hardware acceleration module for speed up of suggested algorithms. Proposed camera calibration method computes extrinsic camera parameters and some of linear intrinsic parameters by solving the perspective transformation matrix. To reduce calibration error, lens distorsion is also taken into account using nonlinear equation optimazation. After the calibration is performed, the recognition of fiducial mark in a SMT board image is proceeded. The SMT board image is represented by boundary information and its key features are extracted. In the recognition process, the fiducial marks are classified among all connected components using a decision tree of the features, and world coordinates of each fiducial mark can be easily computed using calibrated parameters. For the acceleration of suggested algorithms, a DSP board is developed using high speed DSP56001 chip, and two parallel architectures proposed for real-time requirements.
