An Image Granule Labeling Model and Its Implementation

With regard to the absence of base models which are extendible in the field of image analysis,an image granule labeling model is proposed. On the analysis of the applicability of rough sets and quotient space,two new concepts,semantic granule and conception granule,are defined and the image labeling model based on granules is constructed with them. A linear algorithm,Image Granule Labeling(IGL)algorithm,is presented for the realization of the granule labeling model with the definitions of connected segment in a line and potential connection range between two lines. It simplifies connectivity determination using a dynamic set of provisional labels and takes into account the fact that the quantity of granules may be huge and the structure of granules is very complex normally. Comparisons and experimental results on binary images and color images show that the proposed granule labeling algorithm is effective and accurate,and it is quicker than conventional labeling algorithms.