Improved image segmentation techniques for hybrid waveform/object-oriented coding
Peter P. Kauff, Ulrich Goelz, Silko Kruse, S. Rauthenberg · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
A current topic in image coding is to investigate how the efficiency of conventional waveform coding can be improved by utilizing methods from image analysis, image segmentation, image understanding and computer vision. A very promising approach to this problem is object- oriented analysis-synthesis coding and its combination with conventional waveform codecs (hybrid waveform/object-oriented coding). One of the most important key components needed for such a hybrid system is a reliable and generic image segmentation. In this context the underlying contribution presents an algorithm for segmenting objects in front of moving backgrounds. This algorithm is based on four subsequent processing steps which are explained in detail: pre-segmentation by using a Hough transform of conventionally estimated vector fields, global parameter mapping within the pre-segmented background area, compensation of the global background motion, thresholding and post-processing of the remaining DFD signal.