Detecting Salient Blob-Like Image Structures and
Their Scales with a Scale-Space Primal Sketch:
A Method for Focus-of-Attention
Technical report ISRN KTH/NA/P--93/33--SE.
Also in International Journal of Computer Vision,
11(3), 283--318, 1993.
This article presents:
a multi-scale representation of grey-level shape called the
scale-space primal sketch, which makes explicit both features in
scale-space and the relations between structures at different
a methodology for extracting significant blob-like image
structures from this representations, and
applications to edge detection, histogram analysis, and
junction classification demonstrating how the proposed
method can be used for guiding later stage visual processes.
The representation gives a qualitative description of image
structure, which allows for detection of stable scales and
associated regions of interest in a solely bottom-up
In other words, it generates coarse segmentation cues, and
can hence be seen as preceding further processing, which
can then be properly tuned.
It is argued that once such information is available, many
other processing tasks can become much simpler.
Experiments on real imagery demonstrate that the proposed
theory gives intuitive results.
The underlying algorithm for linking blobs (including local extrema and critical points) across scales and registering bifurcation events (singularity points) is described in chapter 9 in Lindeberg (1994) "Scale-Space Theory for Computer Vision", Kluwer Academic Publishers.
Background and related material:
(Monograph on scale-space theory)
(Theory for relating image structures over scales "deep structure")
(Alternative method for multi-scale blob detection and more general methodology for feature detection with automatic scale selection)
(Other publications on scale-space theory)
(Encyclopedia entry on scale-space theory)
Responsible for this page: Tony Lindeberg