1. A hierarchical universal algorithm for geometric objects’ reflection symmetry detectionBorut Žalik, Damjan Strnad, Štefan Kohek, Ivana Kolingerová, Andrej Nerat, Niko Lukač, David Podgorelec, 2022, izvirni znanstveni članek Opis: 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.
Ključne besede: computer science, computational geometry, uniform subdivision, centroids
Objavljeno v DKUM: 01.04.2025; Ogledov: 0; Prenosov: 4
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2. Survey of inter-prediction methods for time-varying mesh compressionJan Dvořák, Filip Hácha, Gerasimos Arvanitis, David Podgorelec, Konstantinos Moustakas, Libor Váša, 2025, izvirni znanstveni članek Opis: Time-varying meshes (TVMs), that is mesh sequences with varying connectivity, are a greatly versatile representation of shapesevolving in time, as they allow a surface topology to change or details to appear or disappear at any time during the sequence.This, however, comes at the cost of large storage size. Since 2003, there have been attempts to compress such data efficiently. Whilethe problem may seem trivial at first sight, considering the strong temporal coherence of shapes represented by the individualframes, it turns out that the varying connectivity and the absence of implicit correspondence information that stems from itmakes it rather difficult to exploit the redundancies present in the data. Therefore, efficient and general TVM compression is stillconsidered an open problem. We describe and categorize existing approaches while pointing out the current challenges in thefield and hint at some related techniques that might be helpful in addressing them. We also provide an overview of the reportedperformance of the discussed methods and a list of datasets that are publicly available for experiments. Finally, we also discusspotential future trends in the field.
Ključne besede: compression algorithms, data compression, modelling, polygonal mesh reduction
Objavljeno v DKUM: 07.02.2025; Ogledov: 0; Prenosov: 2
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4. State-of-the-art trends in data compression : COMPROMISE case studyDavid Podgorelec, Damjan Strnad, Ivana Kolingerová, Borut Žalik, 2024, izvirni znanstveni članek Opis: 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
Ključne besede: data compression, data resoration, universal algorithm, feature, residual
Objavljeno v DKUM: 04.02.2025; Ogledov: 0; Prenosov: 13
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5. A case study on entropy-aware block-based linear transforms for lossless image compressionBorut Žalik, David Podgorelec, Ivana Kolingerová, Damjan Strnad, Štefan Kohek, 2024, izvirni znanstveni članek Opis: Data compression algorithms tend to reduce information entropy, which is crucial, especially in the case of images, as they are data intensive. In this regard, lossless image data compression is especially challenging. Many popular lossless compression methods incorporate predictions and various types of pixel transformations, in order to reduce the information entropy of an image. In this paper, a block optimisation programming framework is introduced to support various experiments on raster images, divided into blocks of pixels. Eleven methods were implemented within , including prediction methods, string transformation methods, and inverse distance weighting, as a representative of interpolation methods. Thirty-two different greyscale raster images with varying resolutions and contents were used in the experiments. It was shown that reduces information entropy better than the popular JPEG LS and CALIC predictors. The additional information associated with each block in is then evaluated. It was confirmed that, despite this additional cost, the estimated size in bytes is smaller in comparison to the sizes achieved by the JPEG LS and CALIC predictors.
Ključne besede: computer science, information entropy, prediction, inverse distance transform, string transformations
Objavljeno v DKUM: 07.01.2025; Ogledov: 0; Prenosov: 10
Celotno besedilo (5,13 MB) |
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8. Geometric Shape Characterisation Based on a Multi-Sweeping ParadigmBorut Žalik, Damjan Strnad, David Podgorelec, Ivana Kolingerová, Andrej Nerat, Niko Lukač, Štefan Kohek, Luka Lukač, 2023, izvirni znanstveni članek Ključne besede: computer science, image analysis, computational geometry, local reflection symmetry
Objavljeno v DKUM: 24.05.2024; Ogledov: 300; Prenosov: 23
Celotno besedilo (1,87 MB)
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9. A new transformation technique for reducing information entropy : a case study on greyscale raster imagesBorut Žalik, Damjan Strnad, David Podgorelec, Ivana Kolingerová, Luka Lukač, Niko Lukač, Simon Kolmanič, Krista Rizman Žalik, Štefan Kohek, 2023, izvirni znanstveni članek Opis: This paper proposes a new string transformation technique called Move with Interleaving (MwI). Four possible ways of rearranging 2D raster images into 1D sequences of values are applied, including scan-line, left-right, strip-based, and Hilbert arrangements. Experiments on 32 benchmark greyscale raster images of various resolutions demonstrated that the proposed transformation reduces information entropy to a similar extent as the combination of the Burrows–Wheeler transform followed by the Move-To-Front or the Inversion Frequencies. The proposed transformation MwI yields the best result among all the considered transformations when the Hilbert arrangement is applied.
Ključne besede: computer science, algorithm, string transformation, information entropy, Hilbert space filling curve
Objavljeno v DKUM: 22.05.2024; Ogledov: 160; Prenosov: 18
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10. FLoCIC: A Few Lines of Code for Raster Image CompressionBorut Žalik, Damjan Strnad, Štefan Kohek, Ivana Kolingerová, Andrej Nerat, Niko Lukač, Bogdan Lipuš, Mitja Žalik, David Podgorelec, 2023, izvirni znanstveni članek Ključne besede: computer science, algorithm, prediction, interpolative coding, PNG, JPEG LS, JPEG 2000 lossless
Objavljeno v DKUM: 22.05.2024; Ogledov: 165; Prenosov: 46
Celotno besedilo (10,78 MB)
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