Adaptive inter frame compression using image segmented technique

Abstract EN

The computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing video image content.

Extracting edge information, which is the essential process in most pictorial pattern recognition problems.

A new method of edge detection technique has been introduces in this research, for detecting boundaries. Selection of typical lossy techniques for encoding edge video images are also discussed in this research.

The concentration is devoted to discuss the Block-Truncation coding technique and Discrete Cosine Transform (DCT) coding technique.

In order to reduce the volume of pictorial data which one may need to store or transmit, the research modifies a method for video image data compression based on the two-component code; in this coding technique, the video image is partitioned into regions of slowly varying intensity.

The contours separating the regions are coded by DCT, while the rest image regions are coded by Block-Truncation Coding.

this hybrid coding technique called segmented image coding (SIC).

Also in this paper A modify of the four step search for motion Estimation technique was produce.

for searching scheme has been introduced which is contributed in decreasing the motion estimation searching time of the successive inter frames.