This study addresses the challenge of reverse engineering binaries from unknown instruction set architectures, a complex task with potential implications for software maintenance and cyber-security. We focus on the tasks of detecting candidate call and return opcodes for automatic extraction of call graphs in order to simplify the reverse engineering process. Empirical testing on a small dataset of binary files from different architectures demonstrates that the approach can accurately detect specific opcodes under conditions of noisy data. The method lays the groundwork for a valuable tool for reverse engineering where the reverse engineer has minimal a priori knowledge of the underlying instruction set architecture.