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Content available Text area detection in handwritten documents scanned for further processing
Pach Jakub Leszek, Krupa Artur, Antoniuk Izabella
Machine Graphics and Vision
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2020
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Vol. 29, No. 1/4
21--31
EN
In this paper we present an approach to text area detection using binary images, Constrained Run Length Algorithm and other noise reduction methods of removing the artefacts. Text processing includes various activities, most of which are related to preparing input data for further operations in the best possible way, that will not hinder the OCR algorithms. This is especially the case when handwritten manuscripts are considered, and even more so with very old documents. We present our methodology for text area detection problem, which is capable of removing most of irrelevant objects, including elements such as page edges, stains, folds etc. At the same time the presented method can handle multi-column texts or varying line thickness. The generated mask can accurately mark the actual text area, so that the output image can be easily used in further text processing steps.
2
Content available Normal Patch Retinex robust algorithm for white balancing in digital microscopy
Roszczyk Radosław, Krupa Artur, Antoniuk Izabella
Machine Graphics and Vision
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2020
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Vol. 29, No. 1/4
79--94
EN
The acquisition of accurately coloured, balanced images in an optical microscope can be a challenge even for experienced microscope operators. This article presents an entirely automatic mechanism for balancing the white level that allows the correction of the microscopic colour images adequately. The results of the algorithm have been confirmed experimentally on a set of two hundred microscopic images. The images contained scans of three microscopic specimens commonly used in pathomorphology. Also, the results achieved were compared with other commonly used white balance algorithms in digital photography. The algorithm applied in this work is more effective than the classical algorithms used in colour photography for microscopic images stained with hematoxylin-phloxine-saffron and for immunohistochemical staining images.
3
Content available remote Optimization of coil geometry using Monte Carlo method with HTCondor and Microsoft Azure technologies
Sawicki Bartosz, Krupa Artur
Przegląd Elektrotechniczny
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2019
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R. 95, nr 5
114--118
EN
The paper presents an application of modern computer services known as cloud computing for the simple coil geometry optimization problem. The Monte Carlo method is known for its robustness, but also low convergence. The latter shortcoming could be eliminated by large and affordable computational power offered today by cloud providers. The described architecture of the simulation system is based on Microsoft Azure platform with HTCondor as a job manager.
PL
Artykuł przedstawia wykorzystanie usług obliczeniowych na przykładzie prostego zagadnienia optymalizacji kształtu cewki. Metoda Monte Carlo jest znana ze swojej skuteczno´sci, a jednocze´snie z bardzo niskiej zbie˙zno´sci. Wad˛et˛a mo ˙ zna skutecznie ograniczy´c poprzez wykorzystaniem du˙zych i tanich mocy obliczeniowych oferowanych dzisiaj przez dostawców usług ’chmurowych’ (ang. cloud computing). Opisana architektura systemu symulacyjnego oparta jest na platformie Microsoft Azure oraz zarz ˛adcy zada´n HTCondor.
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