#ifndef ICLBLOB_H
#define ICLBLOB_H
/**
\mainpage ICLBlob - A package for detection and tracking of image blobs
\section BlobSec Blobs?
An image blob is a connected region of pixels, fulfilling a
homogeneity criteria, like "all pixels have exactly the same color".
The postulation of pairwise connection of the blobs can be softened,
which leads to a more general definition of a blob as an image location
with certain features as mean value, center position, a bounding box, or
its spacial major axis and arcs.
Common classes of this package are:
- ColorBlobSearcher and the DefaultColorBlobSearcher
- PixelRating and PixelRatingGroup
- ImgRegionDetector
- RegionBasedBlobSearcher with FMCreator and RegionFilter
\section AppSec Approaches
The ICLBlob package provides 3 different implementations of
blob detection frameworks, which differ in the way different blobs
are discriminated:
-# The ColorBlobSeacher searches for a set of blobs in an image using a
reference-color and threshold representation for each blob. Blobs are
discriminated by their color; Blobs with identical colors are mixed
together. ( Common classes are: PixelRating, PixelRatingGroup,
ColorBlobSeacher and DefaultColorBlobSearcher )
-# The RegionBasedBlobSearcher also searches for a set of image blobs, which
are discriminated here by their spacial location. The connection
feature is compulsory for blobs. The advantage of this region based approach
is, that it is able to detect a large number of image blobs with identical color.
The drawback is the detected blobs have no kind of ID, which could be
used for blob tracking. (Common classes are: RegionBasedBlobSearcher, FMCreator,
and RegionFilter )
-# The ImgRegionDetector provides low level functionalities for the detection of
connected image regions. The regions that can be found must be connected and
must show identical gray values (color images can not be tackled yet). Commonly the
input image of the ImgRegionDetectors detect(...)-call is a kind of feature
map that shows only a small number of different gray values (see the classes
documentation for more detail). The set of detected image regions can be restricted by:
1st: a min. and max.gray value and 2nd: a min. and max pixel count
Note: The algorithm is highly speed-optimized, by using a special kind of
self implemented memory handling, which avoids memory allocation and deallocation at
runtime if possible. Given large images with O(pixel count) regions (e.g. ordinary
gray images instead of a feature map) the algorithm may need more physical memory than
available. (Common classes are: ImgRegionDetector and the
ICLFilter/LUT::reduceBits(..) function)
*/
#endif