ABSTRACT
Images and video are almost exclusively handled in
compressed formats based on quantized block DCT
transform. Information extraction from images and video
has been traditionally studied in the pixel domain. At
present methods operating in the DCT domain are more
natural and required. There is also argument for DCT
based information extraction based on efficiency:
compressed images preserve perceptually relevant
information at greatly reduced size. This means that all
perceptually non-relevant information is eliminated
which should facilitate information extraction. While
there have been some investigations of pattern
recognition in compressed domain in the past, in this
paper we analyze the problem from the compression and
information reduction perspective. Pattern recognition
method based on optimized quantization of DCT blocks
and density of blocks in regions is introduced and
illustrated on the example of face detection and
recognition problem.