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Evaluating seagrass meadow dynamics by integrating field-based and remote sensing techniques
Danijel Ivajnšič, Martina Orlando-Bonaca, Daša Donša, Jaša Veno Grujić, Domen Trkov, Borut Mavrič, Lovrenc Lipej, 2022, original scientific article

Abstract: Marine phanerogams are considered biological sentinels or indicators since any modification in seagrass meadow distribution and coverage signals negative changes in the marine environment. In recent decades, seagrass meadows have undergone global losses at accelerating rates, and almost one-third of their coverage has disappeared globally. This study focused on the dynamics of seagrass meadows in the northern Adriatic Sea, which is one of the most anthropogenically affected areas in the Mediterranean Sea. Seagrass distribution data and remote sensing products were utilized to identify the stable and dynamic parts of the seagrass ecosystem. Different seagrass species could not be distinguished with the Sentinel-2 (BOA) satellite image. However, results revealed a generally stable seagrass meadow (283.5 Ha) but, on the other hand, a stochastic behavior in seagrass meadow retraction (90.8 Ha) linked to local environmental processes associated with anthropogenic activities or climate change. If systemized, this proposed approach to monitoring seagrass meadow dynamics could be developed as a spatial decision support system for the entire Mediterranean basin. Such a tool could serve as a key element for decision makers in marine protected areas and would potentially support more effective conservation and management actions in these highly productive and important environments.
Keywords: Adriatic Sea, seagrass meadow, change analysis, Cimodocea nodosa, image classifiers, Sentinel-2, marine biology, hydrobiology
Published in DKUM: 17.05.2024; Views: 122; Downloads: 8
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3.
Determining the grain size distribution of granular soils using image analysis
Nihat Dipova, 2017, original scientific article

Abstract: Image-processing technology includes storing the images of objects in a computer and processing them with the computer for a specified purpose. Image analysis is the numerical expression of the images of objects by means of mimicking the functioning of the human visual system and the generation of numerical data for calculations that will be made later. Digital image analysis provides the capability for rapid measurement, which can be made in near-real time, for numerous engineering parameters of materials. Recently, image analysis has been used in geotechnical engineering practices. Grain size distribution and grain shape are the most fundamental properties used to interpret the origin and behaviour of soils. Mechanical sieving has some limitations, e.g., it does not measure the axial dimension of a particle, particle shape is not taken into consideration, and especially for elongated and flat particles a sieve analysis will not yield a reliable measure. In this study the grain size distribution of sands has been determined following image-analysis techniques, using simple apparatus, non-professional cameras and open-code software. The sample is put on a transparent plate that is illuminated with a white backlight. The digital images were acquired with a CCD DSLR camera. The segmentation of the particles is achieved by image thresholding, binary coding and particle labeling. The geometrical measurements of each particle are obtained using an automated pixel-counting technique. Local contacts or limited overlaps were overcome using a watershed split. The same sample was tested by traditional sieve analysis. An image-analysis-based grain size distribution has been compared with a sieve-analysis distribution. The results show that the grain size distribution of the image-based analysis and the sieve analysis are in good agreement.
Keywords: image analysis, image processing, grain size, sand
Published in DKUM: 18.06.2018; Views: 1437; Downloads: 154
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4.
An overview of image analysis algorithms for license plate recognition
Khalid Aboura, Rami Al-Hmouz, 2017, original scientific article

Abstract: 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.
Keywords: image analysis, probabilistic modeling, signal processing, license plate recognition
Published in DKUM: 28.11.2017; Views: 1380; Downloads: 351
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5.
BEHAVIORAL SHIFTS IN THE TRANSLATIONS OF SELECTED PICTURE BOOKS
Metka Lovrin, 2015, master's thesis

Abstract: The purpose of the MA thesis was to explore three English picture books (Sometimes I Like to Curl up in a Ball, The Slurpy Burpy Bear and The Gruffalo) and their Slovene translations (Včasih se rad kotalim kakor žoga, Rigajoči medved and Zverjasec) in regard to inappropriate child behavior which is usually deemed socially unacceptable by adults. Therefore, the aim of my qualitative research was to scrutinize such behavioral occurrences by using comparative and hermeneutic analysis, and to provide inductive reasons with thick description as to why these translation shifts occurred. The empirical part, in which I analyzed relevant sample passages in verbal (and visual) context, has led me to three major categories: “Discrepancy between Childish Authenticity and Social Values”, “Politeness” and “Demonization”. These revealed that corrective changes cannot be applied to Slovene picture book translation in general, but are subject to the individual translator’s child image.
Keywords: Picture book, translation, comparative analysis, inappropriate behavior, child image.
Published in DKUM: 11.08.2016; Views: 1645; Downloads: 154
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Analysis of noise sources produced by faulty small gear units
Aleš Belšak, Jurij Prezelj, 2007, original scientific article

Abstract: Noise source vizualization represents an important tool in the field of technical acoustics. There are many different techniques of noise source visualization. Most of them, however, are intended for a specific noise source in a specific type of acoustic environment. Consequently, a certain visualization method can be used only for certain types of noise sources in a specific acoustic environment and in a restricted frequency area. This paper presents a new visualization method of complex noise sources on the basis of the use of an acoustic camera. A new algorithm has been used, which makes it possible to visualize all types of different complex noise sources. Monopole, dipole or quadropole noise sources can be observed simultaneously. It is possible to track a moving noise source by means of an acoustic camera. In addition to that it is possible to observe various transient acoustical phenomena. Through the use in diagnostics, it is possible to define, by means of noise, the condition of mechanical systems at an advance level.
Keywords: gears, failure, noise sources, visualization of noise sources, sound, acoustic analysis, acoustic camera, signal analysis, acoustic image, measurements
Published in DKUM: 31.05.2012; Views: 2164; Downloads: 42
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8.
Progressive method for color selective edge detection
Peter Rulić, Iztok Kramberger, Zdravko Kačič, 2007, original scientific article

Abstract: Edge detection plays an important role in image analysis systems. We present acolor selective edge detection technique, which consists of two image processing steps. The first step represents pixel-based color detection and the second progressive block-oriented edge detection. The combination of these two steps defines a selective edge detection technique, which enables fast and simple processing of those images captured using arbitrary cameras incomplex scenes with nonstandard illumination. The proposed method was implemented for the detecting of skin color objects and tested on real scene images.
Keywords: image analysis system, image processing, color detection, skin color
Published in DKUM: 31.05.2012; Views: 2078; Downloads: 136
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9.
The complexity of porous structure of building materials
Marko Samec, 2011, dissertation

Abstract: This thesis seeks to establish the link between the structure (in a topological sense) of porous space and charged particle dynamics in porous matter, specifically in constituent elements of sustainable building materials such as clay, cement and soil. The work done is a combination of experimental research and modelling of analysed data using advanced and expanded network models to model pore structure and generalized conductivity model. The main outcome of this doctoral thesis is the demonstration that there is a correlation between the large scale structure of the pore space and the properties of the motion of charged particles through the pore space. This was achieved by conducting two experiments: the structure of pore space of selected porous materials (soil samples, clays, cements, clay-cement mixtures) was investigated using state-of-the-art X-ray computed microtomography, while the dynamics of charged particles in the samples was probed using low-frequency dielectric spectroscopy. The research done and described in the thesis is directed towards the advancement of understanding the transport phenomena and the structure of porous media which is of paramount importance for solving problems in building physics dealing with moist transport in building's envelope, the building-ground interaction, and in transport of contaminants in the vicinity of the repositories where the transfer of moist through soil can be the source of contamination.
Keywords: porous matter, clay-water system, hydrating cement, fractional dynamics, dielectric response, X-ray computed tomography, image analysis, complex network
Published in DKUM: 11.05.2011; Views: 4804; Downloads: 261
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