Performance and capabilities of security forces during operations depend strictly on their ability in gaining information from the desired resources. Therefore, these forces always try to improve their productivity and efficiency using telecommunications and electronic surveillance systems. In surveillance systems, coding detection is done after identification of modulation. Accurate and timely recognition of coding in these systems is so critical that the performance of these systems is tied to it. This paper presents an algorithm that is based on entropy and information theory and is able to detect block and convolution codes. Simulation results show that the proposed algorithm is able to detect coding type in the Additive White Gaussian Noise channels (AWGN) with a minimum signal to noise ratio of 3dB, in binary symmetric channel (BSC) with an error probability of less than 0.1 and in binary erasure channel (BEC) with an error probability of less than 0.2.