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1

De-noising of secured stego-images using AES for various noise types

Ibrahim Gamil Abdel Latif, Saleh Mohamed, Elmahallawy Adham Ahmed

Przegląd Elektrotechniczny

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2023

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R. 99, nr 2

21--26

EN

Steganography plays a crucial part in secret communication systems because information security is a crucial duty in the process of transferring data. However, there are considerable challenges involved in preserving that information, including alteration, privacy, and origin validation. In this paper, the Advanced Encryption Standard (AES) approach and the stenographic method are combined into a reliable model in this study. Furthermore, as Stego-images are acquired or spread across the communication channel, several noise shapes, including additive and multiplicative forms, occur. Therefore, several classes of linear and nonlinear filtering methods are presented and used for noise sweep and stegoimage extraction. The results of the experiments showed that the appropriate assessment metrics were Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Correlation (COR).

PL

Steganografia odgrywa kluczową rolę w systemach tajnej komunikacji, ponieważ bezpieczeństwo informacji jest kluczowym obowiązkiem w procesie przesyłania danych. Jednak z zachowaniem tych informacji wiążą się poważne wyzwania, w tym zmiany, prywatność i weryfikacja pochodzenia. W niniejszym artykule podejście Zaawansowany Standard Szyfrowania (ZSS) i metoda stenograficzna zostały połączone w wiarygodny model w tym badaniu. Ponadto, gdy obrazy Stego są pozyskiwane lub rozprzestrzeniane w kanale komunikacyjnym, pojawia się kilka kształtów szumu, w tym formy addytywne i multiplikatywne. W związku z tym przedstawiono kilka klas liniowych i nieliniowych metod filtrowania, które są wykorzystywane do przemiatania szumów i ekstrakcji obrazów stego. Wyniki eksperymentów wykazały, że odpowiednimi metrykami oceny były błąd średniokwadratowy (Śbk) stosunek sygnału szczytowego do szumu (SWSS) i korelacja (KOR).

2

An Adaptive Richardson-Lucy Algorithm for Medical Image Restoration

Yaqoub Qunoot A., Al-Ani Ayad A.

Journal of Telecommunications and Information Technology

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2023

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nr 1

66--77

EN

Image restoration is the process of estimating the original image content from a degraded picture. In this paper, the Richardson-Lucy iterative algorithm was developed to improve the quality of degraded medical images. It has been assumed that medical images are exposed to two types of degradation. The first type is the blur function in the Gaussian form with different widths, i.e. σ = 1 , 2, and 3. The second type of degradation was assumed to be of the independent white Gaussian noise type with different signal-to-noise ratio values: SNR = 10, 50 , and 100. The results obtained from the adaptive filter are compared, quantitatively, with different conventional filters: inverse, Wiener, and constraint least square, by applying different measures, such as: power signal to noise ratio (PSNR), structural similarity index (SSID), and root mean square error (RMSE). The comparison showed that the adaptive recovery filter achieves better results.

3

A new super resolution Faster R-CNN model based detection and classification of urine sediments

Avci Derya, Sert Eser, Dogantekin Esin, Yildirim Ozal, Tadeusiewicz Ryszard, Plawiak Pawel

Biocybernetics and Biomedical Engineering

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2023

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Vol. 43, no. 1

58--68

EN

The diagnosis of urinary tract infections and kidney diseases using urine microscopy images has gained significant attention of medical community in recent years. These images are usually created by physicians’ own rule of thumb manually. However, this manual urine sediment analysis is usually labor-intensive and time-consuming. In addition, even when physicians carefully examine an image, an erroneous cell recognition may occur due to some optical illusions. In order to achieve cell recognition in low-resolution urine microscopy images with a higher level of accuracy, a new super resolution Faster Region-based Convolutional Neural Network (Faster R-CNN) method is proposed. It aims to increase resolution in low-resolution urine microscopy images using self-similarity based single image super resolution which was used during the pre-processing. Denoising based Wiener filter and Discrete Wavelet Transform (DWT) are used to de-noise high resolution images, respectively, to increase the level of accuracy for image recognition. Finally, for the feature extraction and classification stages, AlexNet, VGFG16 and VGG19 based Faster R-CNN models are used for the recognition and detection of multi-class cells. The model yielded accuracy rates are 98.6%, 96.4% and 96.2% respectively.

4

Low cost blood vein detection system based on near-infrared LEDs and image-processing techniques

Alwazzan Mohammed J.

Polish Journal of Medical Physics and Engineering

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2020

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Vol. 26, Iss. 2

61--67

EN

Drawing blood and injecting drugs are common medical procedures, for which accurate identification of veins is needed to avoid causing unnecessary pain. In this paper, we propose a low-cost system for the detection of veins. The system emits near-infrared radiation from four light-emitting diodes (LEDs), with a charge-coupled device (CCD) camera located in the middle of the LEDs. The camera captures an image of the palm of the hand. A series of digital image-processing techniques, ranging from image enhancement and increased contrast to isolation using a threshold limit based on statistical properties, are applied to effectively isolate the veins from the rest of the image.

5

Stochastic Wiener filter in the white noise space

Alpay Daniel, Pinhas Ariel

Opuscula Mathematica

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2020

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Vol. 40, no. 3

323--339

EN

. In this paper we introduce a new approach to the study of filtering theory by allowing the system's parameters to have a random character. We use Hida's white noise space theory to give an alternative characterization and a proper generalization to the Wiener filter over a suitable space of stochastic distributions introduced by Kondratiev. The main idea throughout this paper is to use the nuclearity of this space in order to view the random variables as bounded multiplication operators (with respect to the Wick product) between Hilbert spaces of stochastic distributions. This allows us to use operator theory tools and properties of Wiener algebras over Banach spaces to proceed and characterize the Wiener filter equations under the underlying randomness assumptions.

6

Image Processing Based Method Evaluating Fabric Structure Characteristics

Shady E., Qashqary K., Hassan M., Militky J.

Fibres & Textiles in Eastern Europe

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2012

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Vol. 20, no. 6A (95)

86--90

EN

A digital image processing approach was developed to evaluate fabric structure characteristics and to recognise the weave pattern utilising a Wiener filter. Images of six different groups were obtained and used for analysis. The groups included three different fabric structures with two different constructions for each. The approach developed decomposed the fabric image into two images, each of which included either warp or weft yarns. Yarn boundaries were outlined to evaluate the fabric surface characteristics and further used to identify the areas of interlaces to detect the fabric structure. The results showed success in evaluating the surface fabric characteristics and detecting the fabric structure for types of fabrics having the same colors of warp and weft yarns. The approach was also able to obtain a more accurate evaluation for yarn spacing and the rational fabric cover factor compared to the analytical techniques used to estimate these characteristics.

PL

Przy zastosowaniu filtra Winera opracowano cyfrową metodę analizy obrazu umożliwiającą ocenę struktury tkanin oraz rozpoznawanie splotu. Zbadano obraz sześciu zróżnicowanych grup tkanin, o 3 rożnych splotach i 2 strukturach, uzyskując dwa obrazy dla każdej tkaniny, z których każdy obejmuje przędze osnowy lub wątku. Wyznaczono wizualne granice nitek osnowy i wątku w celu oceny właściwości powierzchni tkaniny i identyfikacji obszarów przeplotów dla zbadania struktury tkaniny. Badania dla oceny właściwości powierzchni tkaniny i jej struktury dla tkanin o takich samych kolorach przędz wątku i osnowy zakończyły się sukcesem. Dokonano również oceny rozstawu przędzy i współczynnika pokrycia tkaniny i stwierdzono, że metoda ta jest dokładniejsza niż dotychczas stosowane metody analityczne.