Several efficient shape-based recognition methods have been developed to perform object recognition in real time. Some of them focused on shape characterization and landmark point analysis and whole shape matching. A new technique with significantly improved performance for shape matching called Turn-Angle Distribution Analysis (TADA) was developed for fish species recognition (Lee et al., 2008). The TADA approach improved shape-based recognition accuracy, and was the key to the overall effectiveness of the fish recognition system. Based on TADA, a modified version called turn angle cross-correlation similarity measure method specifically for oyster shape evaluation is developed and presented in this paper.