#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