Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensities. In the third stage, the boundary of the target object is extracted, and in the fourth and fifth stages, respectively, the region of interest (ROI) is highlighted and reconstructed. Our model was tested and evaluated using realistic scenarios which include outdoor and indoor scenes. The results reflect the ability of our approach to detect and remove shadows and reconstruct a shadow free image with a small error of approximately 6%.
The lethality of inorganic arsenic (As) and the threat it poses have made the development of efficient As detection systems a vital necessity. This research work demonstrates a sensing layer made of hydrous ferric oxide (Fe2H2O4) to detect As(III) and As(V) ions in a surface plasmon resonance system. The sensor conceptualizes on the strength of Fe2H2O4 to absorb As ions and the interaction of plasmon resonance towards the changes occurring on the sensing layer. Detection sensitivity values for As(III) and As(V) were 1.083 °·ppb−1 and 0.922 °·ppb
Herpes simplex virus (HSV) is a common human pathogen that causes severe infections in newborns and immunocompromised patients. Conjunctivitis or corneal epithelial keratitis is caused by HSV type 1 all over the world and at all times of the year. The present study was aimed at detecting HSV in patients suffering from conjunctivitis. One hundred and ten (110) clinical samples (90 patients and 20 controls, both males and females) of eye conjunctiva swabs were collected from patients of different ages. The samples were analyzed using qPCR and ELISA techniques. The qPCR results revealed that HSV was present in 47 (52.2%) of the 90 patients who were infected. Of these patients, 25 (48.0%) were males and 22 (57.8%) were females, indicati
... Show MoreEchocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.
The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr
... Show MoreIn this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement. The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.