Title :
Novel Noncontrast-Based Edge Descriptor for Image Segmentation
Author :
Kim, Byung-Gyu ; Park, Dong-Jo
Author_Institution :
ETRI, Daejeon
Abstract :
We present an efficient video segmentation strategy based on new edge features to assist object-based video coding, motion estimation, and motion compensation for MPEG-4 and MPEG-7. The proposed algorithm utilizes the human visual perception to provide edge information. Based on the human visual perception, two edge features are introduced and described based on edge features from analysis of a local histogram. An edgeness function is derived to generate the edgeness information map by using the defined features, which can be thought as the gradient image. Then, an improved marker-based region growing and merging techniques are derived to separate the image regions. The proposed algorithm is tested on several standard images and demonstrates high efficiency for object segmentation
Keywords :
data compression; image segmentation; motion compensation; motion estimation; video coding; MPEG-4; MPEG-7; edgeness function; gradient image; human visual perception; image regions; image segmentation; marker-based region growing; merging techniques; motion compensation; motion estimation; noncontrast-based edge descriptor; object segmentation; object-based video coding; video segmentation; Histograms; Humans; Image segmentation; MPEG 4 Standard; MPEG 7 Standard; Merging; Motion compensation; Motion estimation; Video coding; Visual perception; Edge information; histogram analysis; human visual perception; image segmentation; object segmentation;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
DOI :
10.1109/TCSVT.2006.879991