Abstract

Digital video consists of a series of digital images called frames that are displayed in sequence. The whole process of video coding (compression and decompression) requires a codec (encoder-decoder). Encoder compresses data video while decoder decompresses video signal for the user to view. Video compression reduces the data to meet smaller storage requirements or lower transmission bandwidth requirements for clip video content. There are three approaches to perform video compression: intra-frame based, inter-frame based and block-based compression. In this study, inter-frame based compression was performed by applying the feature concept. The aim of this study was to compress frame video through its compressed features using adaptive fuzzy inference system (FIS). Simple features are statistically extracted from each video frame. The features of the two selected frames were used as adaptive FIS training input data. Furthermore, adaptive FIS was used to compress the features of each two adjacent frames into one compressed feature. This feature of compression result then used to generate one compressed frame. The results of this study show that the feature compression technique using adaptive FIS has been successfully used as an inter-frame based video compression. These results also show that the results of the compression ratio determined by the variation of the compressed features generated by the adaptive FIS.

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