DETECTION AND VISUALIZATION OF VISUAL SURFACES ON GPU

V diplomskem delu opišemo algoritem, namenjen zaznavanju vidnih ploskev. Algoritem določi, katere ploskve v sceni so vidne iz izbranega gledišča, pri tem pa učinkovito izrablja grafično procesno enoto (GPE). Za dodatno pospešitev smo uporabili tudi druge, znane, pohitritvene metode, kot sta odstranjevanje objektov, ki ležijo izven vidnega prostora ter hierarhična delitev prostora. S kombiniranjem teh metod smo dobili učinkovito rešitev, ki določi množico vidnih ploskev v realnem času tudi v primeru relativno kompleksne scene.In this diploma thesis we present an algorithm for visible surface detection. The algorithm identifies which surfaces are visible from a viewpoint with the utilization of the graphics processing unit (GPU). In order to maximize the efficiency of the algorithm we use other common speed-up techniques like frustum culling and hierarchical space subdivision. Using a combination of these techniques, an efficient GPU based solution has been obtained. It is able to analyse fairly complex scenes in real time

Optimization of Quasi Distance Transform

V magistrskem delu opisujemo pohitritev transformacije domnevnih razdalj, ki je izpeljanka tradicionalnih algoritmov transformacij razdalj. Transformacije razdalj običajno delujejo nad dvodimenzionalnimi binarnimi slikami, kjer vsakemu elementu ospredja določijo oddaljenost do najbližjega elementa ozadja. Kadar slika ni binarna, je nad njo potrebno izvesti dodano predprocesiranje, ki vključuje korak binarizacije. Nasprotno pa lahko transformacijo domnevnih razdalj uporabimo neposredno nad sivinskimi, barvnimi in multispektralnimi slikami in se tako izognemo pogoste neželenemu predprocesiranju. Slabost tega pristopa pa je časovna zahtevnost, ki je v naivni implementaciji kar O(N^2.5). V magistrskem delu predstavimo pohitren algoritem transformacije domnevnih razdalj ter teoretično analizo njegove časovne zahtevnosti. Nad implementiranim algoritmom izvedemo tudi meritve, s čimer potrdimo teoretične časovne zahtevnosti pohitrenega pristopa, ki je enaka O(N^1.5) v pričakovanem ter O(N^2) v najslabšem primeru.This thesis presents an optimisation of Quasi Distance Transform, derived from traditional distance transformation algorithms. Distance transform is typically applied on two-dimensional binary images, where each foreground element is assigned the distance to its closest background element. When the image is not binary, additional preprocessing with binarisation is required. On the other hand, Quasi Distance Transform can be applied directly to grayscale, colour or multi-spectral images, thus avoiding often unwanted preprocessing. However, the weakness of the method is its time complexity, which is in naive implementation equal to O(N^2.5). In this thesis, we present a new optimised algorithm and the theoretical analysis of its time complexity. We confirm the theoretical time complexity for quasi distance transformation together with measurements, thus proving they are N^(1.5) for the expected and O(N^2) for the worst case

Algorithm for efficient computation of elementary morphological filter chain on central processing unit

V doktorski disertaciji predstavimo nov algoritem za učinkovit izračun verige elementarnih filtrov na centralni procesni enoti. Verige filtrov so temeljni del tako imenovanih geodetskih operatorjev, ki uporabljajo postopek morfološke rekonstrukcije. Ta iterativno filtrira in omejuje vrednosti filtrirane slike. Dobljeno učinkovitost razvitega algoritma delimo na dva dela. Prvi del se zanaša na učinkovit enonitni izračun elementarnih morfoloških filtrov, kar dosežemo s procesiranjem na mestu, dekompozicijo strukturnega elementa in uporabo vektorskih registrov za pohitritev izračuna. Drugi del pa razvite filtre uporabi za učinkovit vzporeden in hkraten izračun več filtrov v podani verigi. Vzporedni izračun je osnovan na emulaciji podatkovno pretokovnega procesiranja, kjer z analizo topologije predpomnilnika CPE in primernim pripenjanjem niti zagotovimo, da prenos podatkov med jedri CPE poteka preko predpomnilnika. Pokazali smo, da dosežemo največjo prepustnost procesiranja ob uporabi več neodvisnih vzporednih procesnih cevovodov, medtem ko najhitrejše odzivne čase dosežemo z uporabo enega cevovoda. Primerjava z algoritmi stanja tehnike in odprtokodnimi knjižnicami je pokazala, da je predlagani algoritem vedno dosegel boljše računske čase pri obdelavi verig filtrov. V primerjavi z iterativnim izračunom verige filtrov na splošnonamenskih grafičnih procesnih enotah se je predlagani algoritem prav tako izkazal za bistveno hitrejšega, tudi ko smo uporabili CPE nižjega cenovnega ranga.In this doctoral dissertation we introduce a new algorithm for efficient calculation of filter chains on central processing unit. Filter chains are a fundamental part of the so-called geodesic operators, which use morphological reconstruction. The latter iteratively filters and bounds the values of the input image. The efficiency of the developed algorithm is compared from two points of view. The first relies on the efficient single-threaded calculation of elementary morphological filters, which is achieved by in-place processing, decomposition of the structuring element and the use of vector registers to speed up calculations. The second part uses the developed filters to efficiently process multiple filters from a given filter chain in parallel. The parallel calculation is based on emulating dataflow processing, where analysis of CPU\u27s cache topology and appropriate thread pinning ensures optimal data transfers between threads via the hierarchical cache. We have shown that the highest processing throughput is achieved using several independent processing pipelines in parallel, while the lowest processing latency is obtained with a single pipeline. A comparison with state-of-the-art algorithms and open source libraries showed that the proposed algorithm always achieves better computational times when processing filter chains. A comparison of computation times of filter chains using general-purpose graphics processing units showed that the proposed algorithm also significantly outperforms them, even when using a lower priced CPU

A Complete Environmental Intelligence System for LiDAR-Based Vegetation Management in Power-Line Corridors

This paper presents the first complete approach to achieving environmental intelligence support in the management of vegetation within electrical power transmission corridors. Contrary to the related studies that focused on the mapping of power lines, together with encroaching vegetation risk assessment, we realised predictive analytics with vegetation growth simulation. This was achieved by following the JDL/DFIG data fusion model for complementary feature extraction from Light Detection and Ranging (LiDAR) derived data products and auxiliary thematic maps that feed an ensemble regression model. The results indicate that improved vegetation growth prediction accuracy is obtained by segmenting training samples according to their contextual similarities that relate to their ecological niches. Furthermore, efficient situation assessment was then performed using a rasterised parametrically defined funnel-shaped volumetric filter. In this way, RMSE≈1 m was measured when considering tree growth simulation, while a 0.37 m error was estimated in encroaching vegetation detection, demonstrating significant improvements over the field observations