The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussian Mixture Model (GMM). This will help find the best way to separate colors in aerial images. According to a thorough comparative study, PSNR and correlation metrics show that K-Medoids outperform other clustering techniques in terms of segmentation quality. Also, the effect of changing the number of clusters on the image quality was studied; when the number of clusters increases, the image quality increases. It was found that when K-Medoids were used, the PSNR and correlation were 35.57 and 0.99, respectively. When FCM and GMM were used, they were 35.54, 0.99, 31.67, and 0.97, respectively, when the number of clusters was 12.
Background: The final stage of endodontic therapy is complete obturation of the root canal system to provide as perfect as possible at the cementodentinal junction of the apical foramen. The purpose of this in vitro study was to evaluate the sealing ability of injection molded thermoplasticized gutta percha and lateral condensation techniques with and without the use of sealers. Materials and Methods: Forty freshly extracted adult human maxillary central incisors with complete formed apices were utilized in this study. The teeth were randomly divided into four groups for evaluation of the apical seal. Group (1) lateral condensation gutta percha technique without sealer, (2) lateral condensation gutta percha technique with sealer, (3) Inject
... Show MoreSoil fertility is a crucial factor in measuring soil quality, it indicates the extent to which soil can support plant life. Soil fertility is measured by the amount of macro and micronutrients, pH, etc. Soil nutrients are depleted after each harvest and therefore must be added. To maintain soil nutrient levels, fertilizer is added to the soil. Adding fertilizer in the precise amount is a matter of great importance because excess or insufficient application can harm plant life and reduce productivity. The use of modern technology is a solution to this problem. Although automated techniques for sowing, weeding, crop harvesting, etc. have been proposed and implemented, none of the techniques are aimed to maintaining soil fertility. The study a
... Show MoreThis study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d
... Show MoreAlpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images
The objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.
The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed sign
This paper presents a meta-heuristic swarm based optimization technique for solving robot path planning. The natural activities of actual ants inspire which named Ant Colony Optimization. (ACO) has been proposed in this work to find the shortest and safest path for a mobile robot in different static environments with different complexities. A nonzero size for the mobile robot has been considered in the project by taking a tolerance around the obstacle to account for the actual size of the mobile robot. A new concept was added to standard Ant Colony Optimization (ACO) for further modifications. Simulations results, which carried out using MATLAB 2015(a) environment, prove that the suggested algorithm outperforms the standard version of AC
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