Image Segmentation using Tensor Voting
Image segmentation entails the division or separation of the image into
regions of similar properties or homogeneous regions.
The commonly used properties for image segmentation are intensity, color
and texture. Homogeneous region extraction is essential for further image
analysis, understanding and interpretation such as object recognition and
moving object tracking.
Most of the segmentation methods use a single property to define
homogeneity and extract regions, while humans perceive regions by the
simultaneous integration of several visual cues. In this talk, we present
a tensor voting based image segmentation method that integrates several
properties naturally in an N-D tensor framework and begets substantial
information for region clustering, and we show promising preliminary