Frejlichowski,D.
Abstract:
In the paper an algorithm for description of greyscale objects extracted from images is applied for recognition of human red blood cells visible on digital microscopic images. This is a part of an approach for automatic (or semi-automatic) diagnosis of selected diseases based on the deformation of erythrocytes. The disease is concluded by means of the recognition of types of red blood cells visible on an digital microscopic image, stained using MGG method and converted into greyscale. The applied algorithm is based on the polar transform of pixels belonging to an object and a specialized method for constituting the resultant description, where derived coordinates are put into matrix, in which the row corresponds to the distance from the centre, and the column — to the angle. This assumption was previously applied only for shape features. The proposed algorithm includes several auxiliary steps, e.g. median and low-pass filtering in order to pre-process the extracted object in greyscale. The algorithm is experimentally evaluated and analysed. It is compared with four other greyscale descriptors, namely: Scale-Invariant Feature Transform, Gabor filter, Polar-Fourier Greyscale Descriptor, and the approach based on polar transform and projections.