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1
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Circular object detection using a modified Hough transform

100%
Smereka M., Dulęba I.
International Journal of Applied Mathematics and Computer Science
|
2008
|
tom 18
|
nr 1
85-91
EN
A practical modification of the Hough transform is proposed that improves the detection of low-contrast circular objects. The original circular Hough transform and its numerous modifications are discussed and compared in order to improve both the efficiency and computational complexity of the algorithm. Medical images are selected to verify the algorithm. In particular, the algorithm is applied to localize cell nuclei of cytological smears visualized using a phase contrast microscope.
2
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Local correlation and entropy maps as tools for detecting defects in industrial images

100%
Skubalska-Rafajłowicz E.
International Journal of Applied Mathematics and Computer Science
|
2008
|
tom 18
|
nr 1
41-47
EN
The aim of this paper is to propose two methods of detecting defects in industrial products by an analysis of gray level images with low contrast between the defects and their background. An additional difficulty is the high nonuniformity of the background in different parts of the same image. The first method is based on correlating subimages with a nondefective reference subimage and searching for pixels with low correlation. To speed up calculations, correlations are replaced by a map of locally computed inner products. The second approach does not require a reference subimage and is based on estimating local entropies and searching for areas with maximum entropy. A nonparametric estimator of local entropy is also proposed, together with its realization as a bank of RBF neural networks. The performance of both methods is illustrated with an industrial image.
3
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Local detection of defects from image sequences

100%
Rafajłowicz E., Wnuk M., Rafajłowicz W.
International Journal of Applied Mathematics and Computer Science
|
2008
|
tom 18
|
nr 4
581-592
EN
Our aim is to discuss three approaches to the detection of defects in continuous production processes, which are based on local methods of processing image sequences. These approaches are motivated by and applicable to images of hot metals or other surfaces, which are uniform at a macroscopic level, when defects are not present. The first of them is based on the estimation of fractal dimensions of image cross-sections. The second and third approaches are compositions of known techniques, which are selected and tuned to our goal. We discuss their advantages and disadvantages, since they provide different information on defects. The results of their testing on 12 industrial images are also summarized.
4
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Recognition of atherosclerotic plaques and their extended dimensioning with computerized tomography angiography imaging

100%
Markiewicz T., Dziekiewicz M., Maruszyński M., Bogusławska-Walecka R., Kozłowski W.
International Journal of Applied Mathematics and Computer Science
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2014
|
tom 24
|
nr 1
33-47
EN
In this paper the authors raise the issue of automatic discrimination of atherosclerotic plaques within an artery lumen based on numerical and statistical thresholding of Computerized Tomography Angiographic (CTA) images and their advanced dimensioning as a support for preoperative vessel assessment. For the study, a set of tomograms of the aorta, as well as the ilio-femoral and femoral arteries were examined. In each case a sequence of about 130-480 images of the artery cutoff planes were analyzed prior to their segmentation based on morphological image transformation. A crucial step in the staging of atherosclerotic alteration is recognition of the plaque in the CTA image. To solve this problem, statistical and linear fitting methods, including the least-squares approximation by polynomial and spline polynomial functions, as well as the error fitting function were used. Also, new descriptors of atherosclerotic changes, such as the lumen decrease factor, the circumference occupancy factor, and the convex plaque area factor, are proposed as a means of facilitating preoperative vessel examination. Finally, ways to reduce the computational time are discussed. The proposed methods can be very useful for automatic quantification of atherosclerotic changes visualized by CTA imaging.
5
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Parallel implementation of local thresholding in Mitrion-C

88%
Kryjak T., Gorgoń M.
International Journal of Applied Mathematics and Computer Science
|
2010
|
tom 20
|
nr 3
571-580
EN
Mitrion-C based implementations of three image processing algorithms: a look-up table operation, simple local thresholding and Sauvola's local thresholding are described. Implementation results, performance of the design and FPGA logic utilization are discussed.
6
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A simultaneous localization and tracking method for a worm tracking system

88%
Kowalski M., Kaczmarek P., Kabaciński R., Matuszczak M., Tranbowicz K., Sobkowiak R.
International Journal of Applied Mathematics and Computer Science
|
2014
|
tom 24
|
nr 3
599-609
EN
The idea of worm tracking refers to the path analysis of Caenorhabditis elegans nematodes and is an important tool in neurobiology which helps to describe their behavior. Knowledge about nematode behavior can be applied as a model to study the physiological addiction process or other nervous system processes in animals and humans. Tracking is performed by using a special manipulator positioning a microscope with a camera over a dish with an observed individual. In the paper, the accuracy of a nematode's trajectory reconstruction is investigated. Special attention is paid to analyzing errors that occurred during the microscope displacements. Two sources of errors in the trajectory reconstruction are shown. One is due to the difficulty in accurately measuring the microscope shift, the other is due to a nematode displacement during the microscope movement. A new method that increases path reconstruction accuracy based only on the registered sequence of images is proposed. The method Simultaneously Localizes And Tracks (SLAT) the nematodes, and is robust to the positioning system displacement errors. The proposed method predicts the nematode position by using NonParametric Regression (NPR). In addition, two other methods of the SLAT problem are implemented to evaluate the NPR method. The first consists in ignoring the nematode displacement during microscope movement, and the second is based on a Kalman filter. The results suggest that the SLAT method based on nonparametric regression gives the most promising results and decreases the error of trajectory reconstruction by 25% compared with reconstruction based on data from the positioning system.
7
Content available remote

A proposition of mobile fractal image decompression

88%
Nikiel S.
International Journal of Applied Mathematics and Computer Science
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2007
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tom 17
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nr 1
129-136
EN
Multimedia are becoming one of the most important elements of the user interface with regard to the acceptance of modern mobile devices. The multimodal content that is delivered and available for a wide range of mobile telephony terminals is indispensable to bind users to a system and its services. Currently available mobile devices are equipped with multimedia capabilities and decent processing power and storage area. The most crucial factors are then the bandwidth and costs of media transfer. This is particularly visible in mobile gaming, where textures represent the bulk of binary data to be acquired from the content provider. Image textures have traditionally added visual realism to computer graphics. The realism increases with the resolution of textures. This represents a challenge to the limited bandwidth of mobile-oriented systems. The challenge is even more obvious in mobile gaming, where single image depicts a collection of shots or animation cycles for sprites and a backdrop scenery. In order to increase the efficiency of image and image texture transfer, a fractal based compression scheme is proposed. The main idea is to use an asymmetric server-client architecture. The resource demanding compression process is performed on the server side while the client part decompresses highly packed image data. The method offers a very high compression ratio for pictures representing image textures for natural scenes. It aims to minimize the transmission bandwidth that should speed up the downloading process and minimize the cost and time of data transfer. The paper focuses on the implementation of fractal decompression schemes suitable for most mobile devices, and opens a discussion on fractal image models for limited resource applications.
8
Content available remote

Notes on a linguistic description as the basis for automatic image understanding

88%
Tadeusiewicz R., Ogiela M., Szczepaniak P.
International Journal of Applied Mathematics and Computer Science
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2009
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tom 19
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nr 1
143-150
EN
The main paradigm of image understanding and a concept for its practical machine realisation are presented. The crucial elements of the presented approach are the formalisation of human knowledge about the class of images that are to be automatically interpreted, a linguistic description and the realization of cognitive resonance.
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