In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

Many image processing and machine learning applications require sufficient image feature selection and representation. This can be achieved by imitating human ability to process visual information. One such ability is that human eyes are much more sensitive to changes in the intensity (luminance) than the color information. In this paper, we present how to exploit luminance information, organized in a pyramid structure, to transfer properties between two images. Two applications are presented to demonstrate the results of using luminance channel in the similarity metric of two images. These are image generation; where a target image is to be generated from a source one, and image colorization; where color information is to be browsed from o

Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and

This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one

Image Fusion Using A Convolutional Neural Network

Background Microorganisms and fungal growth especially Candida albicans, on soft denture lining material are the most common problem which can lead to chronic mucosal inflammation. The aim of this study was to evaluate the effect of zirconium nanoparticles into acrylic-based heat cured soft denture lining material against Candida albicans, and the amount of zirconium ion release of soft liner/ZrNPs composite. Furthermore, evaluate shear bond strength after ZrNPs addition to soft liner. Materials and methods: Zirconium nanoparticles were added into acrylic-based soft denture liner in various percentages (1%, and 1.5% by weight). Two hundred and fifty specimens were arranged and isolated into four groups as per the test to be done The antifu

The objective that the researcher seeks to achieve through this research is to clarify the relationship between strategic management accounting techniques and the reliability of financial statements, and to measure the impact of these techniques as an independent variable with its three dimensions, which are: activities-based cost, target cost, and benchmarking on the reliability of financial statements as a dependent variable. To achieve this objective, the researcher did the following: First: Determine the research problem through the following question: Do strategic management accounting techniques affect the reliability of financial statements in industrial companies listed on the Palestine Exchange? Second: Making the analytical des

This paper presents an experimental study for strengthening existing columns against axial compressive loads. The objective of this work is to study the behavior of concrete square columns strengthening with circulation technique. In Iraq, there are significantly more reinforced rectangular and square columns than reinforced circular columns in reinforced concrete buildings. Moreover, early research studies indicated that strengthening of rectangular or square columns using wraps of CFRP (Carbon Fiber Reinforced Polymer) provided rather little enhancement to their load-carrying capacity. In this paper, shape modification technique was performed to modify the shape (cross section) of the columns from square columns into circular colu

Multi-belled piles are piles with enlarged ends; these piles have one or further bells at the lower third part of the pile. These piles are suitable for many soils with problems such as softening clay, the variation of groundwater table, expansive soils, black cotton soil, and loose sand. The current study reviewed the behavior of belled piles in multi-layer soils subjected to axial compression and pullout loading. The review covered the experimental and theoretical works on belled piles in multi-layered soils. These piles were subjected to static and dynamic loadings in compression and pullout cases. Most theoretical results focused on software such as PLAXIS 3D. The axial load applied on the piles comes from the upper

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number