Abstract:
Gradient-based edge detection is a straightforward
method to identify the edge points in the original greylevel
image. It is intuitive that in the human vision
system the edge points always appear where the greylevel
value is greatly changed Spiral Architecture is a
relatively new image data structure that is inspired
from anatomical considerations of the primate's
vision. In Spiral Architecture, each image is
represented as a collection of hexagonal pixels. Edge
detection on Spiral Architecture has features of fast
computation and accurate localization. In this paper,
we briefly review the edge detection methods on Spiral
Architecture including the edge focusing technique,
bilateral filter, and triple-diagonal gradient. Parallel
algorithms for edge detection will be discussed. We
will also list problems for future work.
