FIELD: method may be used, in particular, for morphologic and texture analysis of material samples being examined, in hematology for example.
SUBSTANCE: in the method a series of digital images of samples is received and transferred into a computer, for each pixel of which images RGB coordinates are determined. Image segmentation is performed, morphological analysis is performed and geometrical characteristics of micro-objects are determined: areas of heterogeneous zones, area of micro-object, shape coefficients of heterogeneous zones, shape coefficient of micro-object, ratio of areas of heterogeneous zones. For each pixel, luminosity L and brightness Y are determined in color models LUV and YUV, matrices of spatial adjacency are computed for each component number K of color image, used as which are: R, G, B from RGB color model, L and Y from LUV and YUV color models, and texture characteristics are determined: energy, inertia momentum, entropy, maximal probability, local homogeneousness. Series length matrices are computed for each component number Q of color image, as which G from RGV color model, L and Y from HLS and YUV color models are used, and texture characteristics of micro-objects are determined: heterogeneousness of brightness, series momentum, reverse series momentum, heterogeneousness of series lengths, share if image in series. Resulting characteristics are compared to characteristics of standard images and membership of the micro-object being analyzed in a certain type is determined.
EFFECT: increased trustworthiness, and also informative value and objectiveness of examination results, reduced laboriousness, expanded functional capabilities of microscopic sample examination.
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Authors
Dates
2007-10-20—Published
2006-10-09—Filed