An effective approach to edge classification from DCT domain

In the field of content-based visual information analysis, the detection of visual features is a significant topic. In order to process video data efficiently, visual features extraction is required. Many advanced video applications require direct manipulation of compressed video data. An effective approach that detects edges in MPEG compressed images is proposed. First, DCT coefficients of 8×8 subblocks are analyzed on their meaning in determining boundaries. Then, we consider two types of ideal linear edges cutting through a block of size 8×8. Based on these edge models, we derive an edge detection approach from ten normalized DCT coefficients, obtaining the general rules of edge classification. Finally, we test the proposed algorithm on different images, and compare our method with other edge classification approaches. Simulations show that our approach can be used to estimate the edge information of images from their DCT coefficients more effectively than those proposed previously.