№2, 2019


Denis G. Privezentsev, Arcady L. Ziznyakov, Yaroslav Y. Kulkov

The objective of the work is to improve the quality of digital image processing in vision systems by developing new features based on the use of fractal theory in conjunction with fuzzy logic and the theory of fuzzy sets. To develop a system of new features, a new model of digital image is needed. It is proposed to modify the fractal model by using a fuzzy distance in it as a measure of similarity of the image areas. This allows you to expand the hierarchy of representations of the source image, thereby increasing the amount of useful information about the original image. The modification of fractal attributes' system is proposed by using the membership function as the main metric, which allows using fuzzy logic in the formation of characteristic values. The proposed new model and a new system of features based on the use of fuzzy measures and membership functions will allow developing new image processing algorithms that differ from the existing possibility of using fuzzy conclusions and results (pp.36-41).

Keywords: images processing, recognition, multiscale analysis, nanostructures.
DOI : 10.25045/jpit.v10.i2.06
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