W artykule przedstawiono propozycje metody wydzielenia cech charakterystycznych z obrazów przedstawiających opłaty pocztowe w celu ich identyfikacji. Zaproponowano algorytm przetwarzania kolorowego obrazu opłaty pocztowej, tak aby pod uwagę były brane te cechy, które zawierają najwięcej dystynktywnych informacji. Dokonano wyboru przestrzeni kolorów z uwzględnieniem wpływu zmian oświetlenia obrazu przesyłek pocztowych na ich reprezentację w przestrzeni cech, zaproponowano dwie nowe metody wydzielania cech obrazu kolorowego. Zwrócono uwagę na problemy związane z przetwarzaniem wstępnym i segmentacją obrazu kolorowego oraz transformacją przestrzeni barw.
EN
The article presents proposals for methods of extracting the characteristics of images to identify them. It proposes a new color image processing algorithms. The choice of color space has impact on changes in light image of postal items to their representation in the feature space. This article proposed two new methods for extracting the characteristics of a color image. It highlights the problems of pre-processing and segmentation color image and color space transformation.
In this paper a novel class of noise attenuating and edge enhancing filters for color image processing is introduced and analyzed. The proposed adaptive filter design is minimizing the cumulative dissimilarity measure of a cluster of pixels belonging to the sliding filtering window and outputs the centrally located pixel. The proposed filter is computationally efficient, easy to implement and very effective in suppressing impulsive noise, while preserving image details and enhancing its edges. Therefore it can be used in any application in which simultaneous denoising and edge enhancement is a prerequisite for further steps of the color image processing pipeline.
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In this paper a novel class of filters designed for the removal of impulsive moise in color images is presented. The proposed filter family is based on the kernel function which controls the noise suppression properties of the proposed filtering scheme. The comparison of the new filtering method with the standard techniques used for impulsive noise removal indicates its superior reduction capabilities and excellent structure preserving properties.
In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply the new noise reduction method for the enhancement of the images of gene chips. We demonstrate that the new technique is capable of reducing various kinds of noise present in microarray images and that it enables efficient spot location and estimation of the gene expression level due to the smoothing effect and preservation of the spot edges. This paper contains the comparison of the new technique of noise reduction with the standard procedures used for the processing of vector valued images, as well as examples of the efficiency of the new algorithm when applied to typical microarray images.
In this paper a new approach to the problem of impulsive noise reduction for color images is introduced. The presented self-adaptive image filter is based on a model of a virtual particle, which performs a random walk on the image lattice, with transition probabilities derived from the Gibbs distribution. The major advantage of the new filtering technique, is that it filters out the noise component, while adapting itself to the local image structures. In this way the new algorithm is able to eliminate strong impulsive noise, while preserving edges and fine image details. As the algorithm is a fuzzy modification of the commonly used vector median operator, it is very fast and easy to implement. Our results show that the proposed method outperforms all standard algorithms of the reduction of impulsive noise in color images.
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A recursive edge tracking of the retinal blood vessel is presented in order to achieve a bidimensionnal reconstruction of the rential vasculature. First, color edge detection is applied on the original angiographic images. Second, from interactive selection of starting points near the papilla, the tracking of the two contours of a vessel is processed. The algorithm validates the next connected pixels to the current ones which satisfy the tracking hypotheses. Problems induced by the curvature of the vessel and the discontinuity of the detected edges will be dealed with. Third, during the tracking procedure is then performed from these branch points until the end of the vessel is reached. Contour and the color of the vessel's body are associated in order to get more accurate extraction. The reconstructed vacular strucures will be used as landmarks for the follow--up of a new retinopathy called CytoMegalo Virus retinitis found on patients with acquired immune deficiency syndrome (AIDS).
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