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Transactions on Intelligent Transportation Systems, 17, 3434-3445, DOI: 10.1109/TITS.2016.2552248 Wojnar, L., 1999. Image analysis. Applications in materials engineering , CRC Press, Boca Raton, USA. Zocca V., Spacagna G., Slater D., Roelants P., 2017. Deep learning. Uczenie głębokie z językiem Python. Sztuczna inteligencja i sieci neuronowe , Helion SA, Gliwice Poland [in Polish]

divider and dynamic image analysis for continuous on-line determination of granule size distribution”, International Journal of Pharmaceutics: X 1, pp. 1 – 7, 2019 . DOI: 10.1016/j.ijpx.2019.100029 [16] Ulusoy, U. “Quantifying of particle shape differences of differently milled barite using a novel technique: Dynamic image analysis”, Materialia 8, 2019 . DOI: 10.1016/j.mtla.2019.100434 [17] Ulusoy, U., Yekeler, M. “Dynamic image analysis of calcite particles created by different mills”, International Journal of Mineral Processing 133, pp. 83 – 90, 2014 . DOI: 10

References [1] Department of Civil Engineering, Yokohama National University, Japan, Image Analysis Techniques on Evaluation of Particle Size Distribution of Gravel , G. H. A. Janaka J. Kumara, Kimitoshi Hayano, Keita Ogiwara. [2] Generalna Dyrekcja Dróg Krajowych i Autostrad, Kruszywa do mieszanek mineralnoasfaltowych i powierzchniowych utrwaleń na drogach krajowych , WT-1 2014 – Kruszywa – Wymagania Techniczne, Załącznik do zarządzenia Nr 46 Generalnego Dyrektora Dróg Krajowych i Autostrad z dnia 25.09.2014 r. [3] Generalna Dyrekcja Dróg Krajowych i Autostrad

matter. Only a digital analysis of the image can eliminate this subjectivity in assessment. 7 Image analysis In the case of yarns with considerably different quality parameters, the assessment of the predicted appearance of woven or knitted fabric, presented by UT5, does not give rise to greater problems, although the criteria of this assessment are of subjective character. On the other hand, in the case of yarns with similar qualitative parameters, the images of the predicted appearance of flat textiles will also be similar and consequently their assessment will not


This paper is a review article which presents examples of application of the image analysis in wood testing. The objective of the paper was to present selected research methods with the use of image analysis used in the research on anatomy and macro-structure of wood carried out in the Department of Forest and Wood Utilization of the Institute of Forest Utilization and Forest Technology of the University of Agriculture in Krakow. In the part concerning research on wood anatomy the following areas of application of the image analysis were indicated: identification of wood species and variability of the selected parameters of the anatomic structure with special attention to coniferous trees. In the part concerning the research on macro-structure of wood, methodology of collection and preparation of wood samples and measurement of the most important properties of the macrostructure was described with the use of the image analysis program. Moreover, the selected areas of practical application of the results of such analysis were indicated.


In order to achieve extended life of asphalt pavement, one of key points is to achieve a good bonding between it’s components. This research paper presents findings on the topic of influence of polyethylene bitumen modification on the adhesion between bitumen and aggregate. A novel method of quantifying the bitumen coated area, based on computer image analysis, has been developed for this study. Two different methods of adhesion testing were employed, namely boiling water method and the rolling bottle method. Aggregates used in this study were granite and limestone. Based on 108 measurements, it was concluded that polyethylene modification has a negative impact on binder aggregate adhesion.

Partikelgrößenanalysen - Teil 1: Grafische Darstellung (ISO 9276-1:1998) (Representation of results of particle size analysis - Part 1: Graphical representation (ISO 9276-1:1998)) Rechberger, C., Prankl, J., Obernberger, G., Handler, F., Prankl, H. (2012). “Automatisierte Bestimmung der Partikellängenverteilung von Grassilagen anhand bildanalytischer Methoden” ( Automated particle length distribution analysis of processed forage by means of image analysis ), in Proceedings of the 70. Internationale Tagung Landtechnik (70 th International Conference Agricultural Engineering), 6


Anodic oxidation of aluminum alloy in a ternary solution of SFS (sulfuric, phthalic and oxalic acids) with 30g of tungsten disulfide (WS2) powder was carried out in order to obtain the aluminum oxide layer named in article as Al2O3/WS2 coatings. The microstructures of surface of obtained coatings were investigated. The subject of the analysis was a threadlike hill structure visible on the surface of coatings as bright ridges. The computer image analysis was performed in order to study the influence of electrolysis time and temperature of acids bath on the volume fraction VV of the area of the surface with filamentous hill’s structure.


Background and purpose: We explore the problem of License Plate Recognition (LPR) to highlight a number of algorithms that can be used in image analysis problems. In management support systems using image object recognition, the intelligence resides in the statistical algorithms that can be used in various LPR steps. We describe a number of solutions, from the initial thresholding step to localization and recognition of image elements. The objective of this paper is to present a number of probabilistic approaches in LPR steps, then combine these approaches together in one system. Most LPR approaches used deterministic models that are sensitive to many uncontrolled issues like illumination, distance of vehicles from camera, processing noise etc. The essence of our approaches resides in the statistical algorithms that can accurately localize and recognize license plate.

Design/Methodology/Approach: We introduce simple and inexpensive methods to solve relatively important problems, using probabilistic approaches. In these approaches, we describe a number of statistical solutions, from the initial thresholding step to localization and recognition of image elements. In the localization step, we use frequency plate signals from the images which we analyze through the Discrete Fourier Transform. Also, a probabilistic model is adopted in the recognition of plate characters. Finally, we show how to combine results from bilingual license plates like Saudi Arabia plates.

Results: The algorithms provide the effectiveness for an ever-prevalent form of vehicles, building and properties management. The result shows the advantage of using the probabilistic approached in all LPR steps. The averaged classification rates when using local dataset reached 79.13%.

Conclusion: An improvement of recognition rate can be achieved when there are two source of information especially of license plates that have two independent texts.


Segregation of shredded waste is one of the technologies of waste management, along with issues related to manual segregation, while nowadays it starts to be associated with pneumatic classification. This paper discusses the use of an air classifier and image analysis techniques for the purposes of evaluation of segregation of shredded waste. This type of air classifier plays an important role due to the efficiency of the device and the characteristics of segregation. The authors report the results of research into image analysis of segregation of shredded waste on the basis of the use of image analysis.