Classification of Image Codecs in Telecommunication Networks

Nowadays, with the spread of communication networks, the demand to transmit multimedia data has significantly increased. So, the knowledge about data type which is transmitted through the network is an important issue for monitoring communications and preventing transmission of malicious data. A typical identification system attempts to identify the type of transmitted coded data through classification within a predefined set. The classification is usually based on some relevant features extracted from the received bit stream. Most of the researches in this field consider a few kinds of image codec in their classification problem. In this paper, an efficient identification system is proposed for classification within ten different images codecs. The proposed system is based on combination and extension of existing methods. According to simulation results, image codecs are classified with average accuracy of 88.90%. Among various codecs, GIF and BMP have the highest accuracy of 99.3% and 92.5%, respectively. On the other hand, FLIF and WEBP have the lowest accuracy 83.3% and 83.6%, respectively.