1. Approximate local reflection symmetry of projected land cadastre dataIvana Kolingerová, Ondřej Anděl, Eliška Mourycová, Pavel Slavík, Lukáš Hruda, David Podgorelec, Borut Žalik, Ivo Malý, Martin Maňák, 2025, original scientific article Abstract: Symmetry is an essential feature of many geometric objects. However, the world also contains many asymmetrical or approximately symmetrical objects. Detecting approximate symmetries is a rather weakly defined problem, as computer-detected approximate symmetry may not correspond to human opinion. The situation is even worse if the symmetry is not global but local. This paper investigates whether approximate local reflection symmetries found by a computer in real data are acceptable for human observers. To answer this question, a new simple approximate local reflection symmetry detection is proposed and run on land cadastre data in the form of planar point sets. The resulting symmetries are subject to user tests to study human acceptance of approximate local symmetry. The results show a relatively good correlation between symmetry detected by computers and perceived by humans. This finding provides a solid foundation for integrating both approaches in specific applications. To achieve this, further research is needed on how to utilize specific aspects of human symmetry perception in computer solutions, so that computer symmetry detection can better approximate human perception.
Keywords: symmetry, geodata, computer graphics, human perception
Published in DKUM: 09.12.2025; Views: 0; Downloads: 1
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2. Challenges in algorithmic implementation : the FLoCIC algorithm as a case study in tehnology-enhanced computer science educationDavid Jesenko, Borut Žalik, Štefan Kohek, 2025, original scientific article Abstract: Learning and implementing algorithms is a fundamental but challenging aspect of Computer Science education. One of the key tools used in teaching algorithms is pseudocode, which serves as an abstract representation of the logic behind a given algorithm. This study explores the educational value of the FLoCIC (Few Lines of Code for Image Compression) algorithm, which is designed to teach lossless image compression through algorithmic implementation, particularly within the context of multimedia data. Image compression represents a typical multimedia task that combines algorithmic thinking with practical problem-solving. By analysing questionnaire responses (N = 121) from undergraduate and graduate students, this study identifies critical challenges in pseudocode-based learning, including understanding complex algorithmic components and debugging recursive functions. This paper highlights the influence of prior knowledge in areas such as data structures, compression, and algorithms in general on the success of students in completing the task, with graduate students demonstrating stronger results compared to undergraduates. The study analyses the role of external resources and online code repositories, further revealing their utility in supporting implementation efforts but highlighting the need for a fundamental understanding of the algorithm for successful implementation. The findings highlight the importance of promoting conceptual understanding and practical problem-solving skills to improve student learning in algorithmic tasks.
Keywords: FLoCIC, computer science, algorithms, pseudocode, coding, generative AI, multimedia, education
Published in DKUM: 02.10.2025; Views: 0; Downloads: 12
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3. Uvod v računalniško večpredstavnost in obdelavo multimedijskih podatkovŠtefan Kohek, Borut Žalik, 2025, reviewed university, higher education or higher vocational education textbook Abstract: Ta učbenik je namenjen študentom prve stopnje študijskega programa Računalništvo in informacijske tehnologije ter zajema vsebino predmetov Multimedia in Računalniška večpredstavnost. Učbenik opisuje osnovne vidike multimedije, multimedijskih tipov, njihovih formatov in operacij nad njimi. Ponuja postopen in sistematičen pregled temeljnih konceptov obdelave multimedijskih podatkov. Poseben poudarek je na predstavitvi osnovnih tipov multimedijskih podatkov, izbranih algoritmov za njihovo obdelavo in najpogostejših multimedijskih formatov. Struktura učbenika sledi osnovnim tipom multimedijskih podatkov, in sicer tekstu, slikam, digitalnemu avdiu in videu. Vsako poglavje se zaključi z naborom vprašanj in praktičnih nalog za poglobljeno razumevanje obravnavane snovi.
Keywords: računalniška večpredstavnost, multimedija, multimedijski podatki, formati datotek, avdio, video, tekst, slike, učbeniki
Published in DKUM: 09.09.2025; Views: 0; Downloads: 18
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4. Detection and optimization of photovoltaic arrays’ tilt angles using remote sensing dataNiko Lukač, Sebastijan Seme, Klemen Sredenšek, Gorazd Štumberger, Domen Mongus, Borut Žalik, Marko Bizjak, 2025, original scientific article Abstract: Maximizing the energy output of photovoltaic (PV) systems is becoming increasingly important. Consequently, numerous approaches have been developed over the past few years that utilize remote sensing data to predict or map solar potential. However, they primarily address hypothetical scenarios, and few focus on improving existing installations. This paper presents a novel method for optimizing the tilt angles of existing PV arrays by integrating Very High Resolution (VHR) satellite imagery and airborne Light Detection and Ranging (LiDAR) data. At first, semantic segmentation of VHR imagery using a deep learning model is performed in order to detect PV modules. The segmentation is refined using a Fine Optimization Module (FOM). LiDAR data are used to construct a 2.5D grid to estimate the modules’ tilt (inclination) and aspect (orientation) angles. The modules are grouped into arrays, and tilt angles are optimized using a Simulated Annealing (SA) algorithm, which maximizes simulated solar irradiance while accounting for shadowing, direct, and anisotropic diffuse irradiances. The method was validated using PV systems in Maribor, Slovenia, achieving a 0.952 F1-score for module detection (using FT-UnetFormer with SwinTransformer backbone) and an estimated electricity production error of below 6.7%. Optimization results showed potential energy gains of up to 4.9%.
Keywords: solar energy, photovoltaics, semantic segmentation, optimization, LiDAR, VHR imagery
Published in DKUM: 22.07.2025; Views: 0; Downloads: 12
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5. Compression of triangulated solids’ surfaces by Decimating Reconstructable TrianglesBlaž Repnik, Borut Žalik, Krista Rizman Žalik, 2025, original scientific article Abstract: This paper introduces a new programming solution for reducing the size of files needed to store 3D geometric solids, whose surfaces are interpolated by watertight irregular triangle meshes. Unlike other approaches, the software does not introduce any special storage data format, but, instead, utilises popular CAD formats such as STL, OBJ, or PLY. This increases the software’s interoperability significantly. The software comprises an encoder and a decoder. The encoder estimates which facets may be removed in such a way that they can later be reconstructed unambiguously by the decoder. The decoder also ensures that the reconstructed triangles are oriented correctly. The encoder and the decoder are straightforward to understand and to implement. They are asymmetric, making any potential programming error easier to identify and correct.
Keywords: data compression, geometric modelling, computer-aided design, boundary representation, topology, watertightness
Published in DKUM: 30.05.2025; Views: 0; Downloads: 2
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6. An algorithm for voxelised solids representation using chain codesBlaž Repnik, Libor Váša, Borut Žalik, 2025, original scientific article Abstract: The paper introduces a new method to describe the surfaces of voxelised solids. It operates in three stages: a hierarchical linked list of chain code sequences is created first; the linked lists are pruned; and, finally, the content of the data structure is stored. The method uses chain codes from either a three- or nine-symbols alphabet. In the first case, two chain code symbols are needed to access the next face, while, in the second case, this is done by one symbol. The pair of chain codes from the three-symbols alphabet, or the individual symbol from the nine-symbols alphabet are considered as tokens. The sets of tokens are, in both cases, extended by two tokens, indicating the beginning and ending of the list. The method processes solids of any shape, including those containing holes, cavities, or multiple components existing in the same voxel space. Edge-connectivity is permitted. The method was compared against the method proposed by Lemus et al., which is designed for solids without holes. Although supporting a broader set of voxelised solids, the proposed method generates sequences of tokens that are, on average, up to 10% shorter. Since the information entropy of the sequences of tokens produced by the proposed method is also smaller, the obtained sequences are more compressible, as confirmed by applying gzip and bzip2 data compressors.
Keywords: voxels, chain code, data structures, pruning, information entropy, data compression
Published in DKUM: 19.05.2025; Views: 0; Downloads: 3
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7. A hierarchical universal algorithm for geometric objects’ reflection symmetry detectionBorut Žalik, Damjan Strnad, Štefan Kohek, Ivana Kolingerová, Andrej Nerat, Niko Lukač, David Podgorelec, 2022, original scientific article Abstract: A new algorithm is presented for detecting the global reflection symmetry of geometric
objects. The algorithm works for 2D and 3D objects which may be open or closed and may or may
not contain holes. The algorithm accepts a point cloud obtained by sampling the object’s surface at
the input. The points are inserted into a uniform grid and so-called boundary cells are identified.
The centroid of the boundary cells is determined, and a testing symmetry axis/plane is set through
it. In this way, the boundary cells are split into two parts and they are faced with the symmetry
estimation function. If the function estimates the symmetric case, the boundary cells are further split
until a given threshold is reached or a non-symmetric result is obtained. The new testing axis/plane
is then derived and tested by rotation around the centroid. This paper introduces three techniques to
accelerate the computation. Competitive results were obtained when the algorithm was compared
against the state of the art.
Keywords: computer science, computational geometry, uniform subdivision, centroids
Published in DKUM: 01.04.2025; Views: 0; Downloads: 8
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8. STALITA: innovative platform for bank transactions analysisDavid Jesenko, Štefan Kohek, Borut Žalik, Matej Brumen, Domen Kavran, Niko Lukač, Andrej Živec, Aleksander Pur, 2022, original scientific article Abstract: Acts of fraud have become much more prevalent in the financial industry with the rise
of technology and the continued economic growth in modern society. Fraudsters are evolving
their approaches continuously to exploit the vulnerabilities of the current prevention measures
in place, many of whom are targeting the financial sector. To overcome and investigate financial
frauds, this paper presents STALITA, which is an innovative platform for the analysis of bank
transactions. STALITA enables graph-based data analysis using a powerful Neo4j graph database
and the Cypher query language. Additionally, a diversity of other supporting tools, such as support
for heterogeneous data sources, force-based graph visualisation, pivot tables, and time charts, enable
in-depth investigation of the available data. In the Results section, we present the usability of the
platform through real-world case scenarios.
Keywords: Neo4j, platform, bank transactions, graph analysis, graph visualisation, fraud, investigation
Published in DKUM: 27.03.2025; Views: 0; Downloads: 22
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9. State-of-the-art trends in data compression : COMPROMISE case studyDavid Podgorelec, Damjan Strnad, Ivana Kolingerová, Borut Žalik, 2024, original scientific article Abstract: After a boom that coincided with the advent of the internet, digital cameras, digital video and audio storage and playback devices, the research on data compression has rested on its laurels for a quarter of a century. Domain-dependent lossy algorithms of the time, such as JPEG, AVC, MP3 and others, achieved remarkable compression ratios and encoding and decoding speeds with acceptable data quality, which has kept them in common use to this day. However, recent computing paradigms such as cloud computing, edge computing, the Internet of Things (IoT), and digital preservation have gradually posed new challenges, and, as a consequence, development trends in data compression are focusing on concepts that were not previously in the spotlight. In this article, we try to critically evaluate the most prominent of these trends and to explore their parallels, complementarities, and differences. Digital data restoration mimics the human ability to omit memorising information that is satisfactorily retrievable from the context. Feature-based data compression introduces a two-level data representation with higher-level semantic features and with residuals that correct the feature-restored (predicted) data. The integration of the advantages of individual domain-specific data compression methods into a general approach is also challenging. To the best of our knowledge, a method that addresses all these trends does not exist yet. Our methodology, COMPROMISE, has been developed exactly to make as many solutions to these challenges as possible inter-operable. It incorporates features and digital restoration. Furthermore, it is largely domain-independent (general), asymmetric, and universal. The latter refers to the ability to compress data in a common framework in a lossy, lossless, and near-lossless mode. COMPROMISE may also be considered an umbrella that links many existing domain-dependent and independent methods, supports hybrid lossless–lossy techniques, and encourages the development of new data compression algorithms
Keywords: data compression, data resoration, universal algorithm, feature, residual
Published in DKUM: 04.02.2025; Views: 0; Downloads: 15
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10. Efficient compressed storage and fast reconstruction of large binary images using chain codesDamjan Strnad, Danijel Žlaus, Andrej Nerat, Borut Žalik, 2024, original scientific article Abstract: Large binary images are used in many modern applications of image processing. For instance, they serve as inputs or target masks for training machine learning (ML) models in computer vision and image segmentation. Storing large binary images in limited memory and loading them repeatedly on demand, which is common in ML, calls for efficient image encoding and decoding mechanisms. In the paper, we propose an encoding scheme for efficient compressed storage of large binary images based on chain codes, and introduce a new single-pass algorithm for fast parallel reconstruction of raster images from the encoded representation. We use three large real-life binary masks to test the efficiency of the proposed method, which were derived from vector layers of single-class objects – a building cadaster, a woody vegetation landscape feature map, and a road network map. We show that the masks encoded by the proposed method require significantly less storage space than standard lossless compression formats. We further compared the proposed method for mask reconstruction from chain codes with a recent state-of-the-art algorithm, and achieved between and faster reconstruction on test data
Keywords: binary mask, machine learning, chain code, binary encoding, bitmap reconstruction
Published in DKUM: 29.01.2025; Views: 0; Downloads: 154
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