Constrained Spectral Uplifting

Fyzikálne založený spektrálny rendering sa stáva čoraz viac populárnym ako v komerčnej, tak aj v akademickej sfére kvôli jeho schopnosti presne simulovať prírodné fenomény. Bohužiaľ, vytváranie materiálov definovaných ich spektrálnymi vlastnosťami je drahý a zdĺhavý proces, a teda využívanie materiálov založených na RGB reprezentácii je žiadaná vlastnosť v spektrálnych rendereroch. Na konvertovanie RGB hodnôt do ich spektrálnych variánt sa využíva proces nazývaný spektrálny uplifting. Nakoľko je RGB farebný priestor konečnou podmnožinou viditeľného gamutu, existuje mnoho konvertovacích techník dodávajúcich rôzne výsledky, ktoré môžu za odlišných svetelných podmienok spôsobovať farebné nezrovnalosti. Táto práca navrhuje metódu na obmedzenie procesu spektrálneho upliftingu. Presne povedané, preddefinované mapovania z RGB hodnôt na ich spektrálne reprezentácie sú zachované a zvyšok RGB gamutu je vierohodne konvertovaný. Na to, aby sme posúdili správnosť tejto techniky, ju implementujeme a evaluujeme v spektrálnom rendereri. Obrázky konvertované našou metódou vykazujú v porovnaní s pôvodnými textúrami minimálne nezrovnalosti.Physically-based spectral rendering is becoming increasingly popular in both commercial and academic areas due to its ability to accurately simulate natural phenomena. However, the production of materials defined by their spectral properties is a tedious and expensive process, which makes the utilization of RGB-based assets in spectral renderers a desired feature. To convert RGB values to their spectral representations, a process called spectral uplifting is employed. As the RGB color space is a finite subset of the visible gamut, there exist multiple conversion techniques producing distinct results, which may cause color inconsistencies under various lighting conditions. This thesis proposes a method for constraining the spectral uplifting process. To be specific, pre-defined mappings of RGB values to their spectral representations are preserved and the rest of the RGB gamut is plausibly uplifted. In order to assess its correctness, this technique is then implemented and evaluated in a spectral renderer. The renders uplifted via our method show minimal discrepancies when compared to the original textures.Department of Software and Computer Science EducationKatedra softwaru a výuky informatikyMatematicko-fyzikální fakultaFaculty of Mathematics and Physic

Constrained Spectral Uplifting

Physically-based spectral rendering is becoming increasingly popular in both commercial and academic areas due to its ability to accurately simulate natural phenomena. However, the production of materials defined by their spectral properties is a tedious and expensive process, which makes the utilization of RGB-based assets in spectral renderers a desired feature. To convert RGB values to their spectral representations, a process called spectral uplifting is employed. As the RGB color space is a finite subset of the visible gamut, there exist multiple conversion techniques producing distinct results, which may cause color inconsistencies under various lighting conditions. This thesis proposes a method for constraining the spectral uplifting process. To be specific, pre-defined mappings of RGB values to their spectral representations are preserved and the rest of the RGB gamut is plausibly uplifted. In order to assess its correctness, this technique is then implemented and evaluated in a spectral renderer. The renders uplifted via our method show minimal discrepancies when compared to the original textures

OCR for tabular data

Table recognition is an important tool for digitalizing documents that con- tain tabular data, which often occur in areas of administration, finances and education. This thesis re-uses existing optical character recognition software to construct a new table recognition algorithm that aims to simplify the digitaliza- tion of diverse document types. The resulting algorithm achieves comparable or better results than currently available open-source software. Thesis additionally reviews common methods of OCR software implementation, and measures the influence of image preprocessing quality on the outcome of the table recognition.

OCR pro tabulková data

Rozpoznávanie tabuliek je dôležitým nástrojom pre digitalizáciu tabu- ľkových dokumentov, ktoré sa bežne využívajú v oblastiach administratívy, bankovníctva a vzdelávania. Cieľom práce je za pomoci existujúceho soft- véru na optické rozpoznávanie znakov (OCR) implementovať nový algoritmus na rozpoznávanie tabuliek pre zjednodušenie digitalizácie rôznorodých doku- mentov. V porovnaní s dnešnými open-source softvérmi dosahuje výsledný algoritmus porovnateľné alebo lepšie výsledky. Práca navyše dokumentuje rôzne implementácie OCR a meria vplyv kvality predspracovania obrázku na rozpoznávanie tabuliek.Table recognition is an important tool for digitalizing documents that con- tain tabular data, which often occur in areas of administration, finances and education. This thesis re-uses existing optical character recognition software to construct a new table recognition algorithm that aims to simplify the digitaliza- tion of diverse document types. The resulting algorithm achieves comparable or better results than currently available open-source software. Thesis additionally reviews common methods of OCR software implementation, and measures the influence of image preprocessing quality on the outcome of the table recognition. 1Department of Software EngineeringKatedra softwarového inženýrstvíMatematicko-fyzikální fakultaFaculty of Mathematics and Physic