Robotic vision has become a very popular field in recent years due to the numerous promising applications it may enhance. However, errors within the cameras and in their perception of their environment can cause applications in robotics to fail. To help correct these internal and external imperfections, stereo camera calibrations are performed. There are currently many accurate methods of camera calibration available; however, most or all of them are time consuming and labor intensive. This research seeks to automate the most labor intensive aspects of a popular calibration technique developed by Jean-Yves Bouguet. His process requires manual selection of the extreme corners of a checkerboard pattern. The modified process uses embedded LEDs in the checkerboard pattern to act as active fiducials. Images are captured of the checkerboard with the LEDs on and off in rapid succession. The difference of the two images automatically highlights the location of the four extreme corners, and these corner locations take the place of the manual selections. With this modification to the calibration routine, upwards of eighty mouse clicks are eliminated per stereo calibration. Preliminary test results indicate that accuracy is not substantially affected by the modified procedure. Improved automation to camera calibration procedures may finally penetrate the barriers to the use of calibration in practice.