Abstarct: Video compression is one of the most important areas of research and commercial domains in computer science. With the advent of video in a web context, due to limited communication bandwidth, the growing demand for video compression has emerged. One of the most important areas to transfer video contents over the web platform is in the field of distance learning. The video contents are either online or pre-recorded to be transferred on the web. Due to the limited bandwidth and high size of video frxames, video compression is a necessary solution. By reducing the size of a video frxame, it can be easily transferred over the web, and associate the remaining bandwidth to sound or other additional information. The challenge in the areas of video compression codecs is to provide higher quality frxames with smaller size and the most compact possible. In this thesis, the focus is towards to video compression for sedentary video frxames in distance learning applications and a codec is proposed to compress and transfer with a higher rate. In this codec, all the redundancies of the video frxames are removed at the first place. Then, by the help of image segmentation in each frxame, redundancy is eliminated due to the fact that some parts of the frxame does not change in a frxame sequence. This action increases the compression rate of the video without having to harm the image pixel value and reduces the quality of the produce. It can be claimed that video compression rate for distance learning is increased against to other methods which are applicable to stirring video frxames. The main objective of this thesis is to provide a unique video compression for distance learning application. The proposed codec for video compression has a high compression rate and will not affect the quality of moving parts of the video frxames.