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EN
Structural image features are exploited to construct perceptual image hashes in this work. The image is first preprocessed and divided into overlapped blocks. Correlation between each image block and a reference pattern is calculated. The intermediate hash is obtained from the correlation coefficients. These coefficients are finally mapped to the interval [0, 100], and scrambled to generate the hash sequence. A key component of the hashingmethod is a specially defined similarity metric to measure the "distance" between hashes. This similarity metric is sensitive to visually unacceptable alterations in small regions of the image, enabling the detection of small area tampering in the image. The hash is robust against content-preserving processing such as JPEG compression, moderate noise contamination, watermark embedding, re-scaling, brightness and contrast adjustment, and low-pass filtering. It has very low collision probability. Experiments are conducted to show performance of the proposed method.
EN
The object of the studies presented in this paper were the samples of mineral fillers obtained from a dust extractor of asphalt plant as well as mastics containing these fillers. The work consists of two parts. In the first part a comparative analysis of the structural and functional properties of the limestone, basaltic and melaphyrc fillers was carried out. To this end, the grain-size distribution, specific surface area, Rigden voids as well as bulk volume concentration and activity index of fillers were determined. In the second part, quantitative and qualitative estimations of the stiffening properties of these fillers in mastics were performed. A search for the quantitative relationship between the filler's structural features and the selected rheological properties of mastics was conducted in order to assess a practicability of dusts obtained from a dust extractor of asphalt plant to use in asphalt pavement layers.
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