An Improved Star Detection Algorithm Using a Combination of Statistical and Morphological Image Processing Techniques

2018 ◽  
Author(s):  
Samed AL ◽  
Irfan Karagoz ◽  
Ali Dogan
Keyword(s):  
Image Processing ◽  
Detection Algorithm ◽  
Image Processing Techniques ◽  
Morphological Image Processing ◽  
Processing Techniques ◽  
Morphological Image

scholarly journals Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy-Based Image Processing Techniques

2020 ◽  
Vol 9 (3) ◽  
pp. 2251-2256
Keyword(s):  
Image Processing ◽  
Composite System ◽  
Detection Method ◽  
Research Work ◽  
Detection Algorithm ◽  
Image Processing Techniques ◽  
Sensitivity Specificity ◽  
Processing Techniques ◽  
Retinal Fundus ◽  
Retinal Drusen

Drusen identification is the fundamental operation in the automated diagnosis of eye diseases. Manual and automatic detection of the drusen in the retinal fundus images has been developed recently in the classical manner only. This work provides the quantum-based retinal drusen detection method using entropy-based image processing techniques. This algorithm is the composite system of two channels, classical and quantum channels for the preprocessing and drusen detection respectively. This research work has been evaluated with the databases of DRIVE, STARE, MESSIDOR, E-Optha-Ex and ONH-Hunter. This quantum-based approach will be analyzed with the results of the existing classical methods and proves its efficiency from the calculations of sensitivity, specificity, accuracy and execution time.

scholarly journals Detecção de Vagas em Estacionamento Usando Visão Computacional e Redes Neurais Convolucionais

2020 ◽  
Author(s):  
Caroline Mazetto Mendes ◽  
Willian Marrion Cavenagli
Keyword(s):  
Image Processing ◽  
Detection Algorithm ◽  
Parking Space ◽  
Urban Mobility ◽  
Parking Lots ◽  
Image Processing Techniques ◽  
Mobility Problem ◽  
Processing Techniques

Parking lots are no longer practical solutions but become anothertopic of urban mobility problem due to the difficulty in finding availableparking spaces. This work proposes a parking space detectionsystem to assist drivers. The system detects unoccupied vacanciesby image processing techniques and convolutional neural networks.Vacancies are detected through horizontal markings and by recognizingspaces with or without vehicles. Finally, a mobile applicationmakes available to the user the occupancy status of vacancies. Initialresults showed that the system detects vacancies with visiblemarkings during the daytime. To improve detection in adversesituations, the vacancy detection algorithm is being improved.

scholarly journals Auto_Bot for Fire Detection and Extinguishion

2019 ◽  
Vol 8 (4) ◽  
pp. 5224-5226
Keyword(s):  
Image Processing ◽  
Mobile Robot ◽  
Temperature Sensor ◽  
Fire Detection ◽  
Detection Algorithm ◽  
Smoke Detector ◽  
Set Point ◽  
Image Processing Techniques ◽  
Processing Techniques

In this paper, we proposed a fire detection algorithm to detect fire based on image processing techniques. This is compatible in surveillance device like CCTV, wireless camera. Video - Based Fire Detection are not mobilised and autonomous. The camera is turnedON only when the sensors reach a particular set point from temperature sensor and smoke detector. The captured video is converted to frames and image processing is done to identify the fire by means of its unique characteristics like Color, Motion and Flickering of flamesas these features are powerful discriminants. Suitable image processing techniques are applied to detect the fire.If the fire is identified, a mobile robot consists of water hoses is actuated to put off the fire

Let The Sunshine in: Sun Glare Detection on Automotive Surround-view Cameras

2020 ◽  
Vol 2020 (16) ◽  
pp. 80-1-80-9 ◽  
Author(s):  
Lucie Yahiaoui ◽  
Michal Uřičář ◽  
Arindam Das ◽  
Senthil Yogamani
Keyword(s):  
Image Processing ◽  
Visual Perception ◽  
Detection Algorithm ◽  
Automated Driving ◽  
Driving System ◽  
Global Context ◽  
Image Processing Techniques ◽  
Public Dataset ◽  
Classical Image ◽  
Processing Techniques

Sun glare is a commonly encountered problem in both manual and automated driving. Sun glare causes over-exposure in the image and significantly impacts visual perception algorithms. For higher levels of automated driving, it is essential for the system to understand that there is sun glare which can cause system degradation. There is very limited literature on detecting sun glare for automated driving. It is primarily based on finding saturated brightness areas and extracting regions via image processing heuristics. From the perspective of a safety system, it is necessary to have a highly robust algorithm. Thus we designed two complementary algorithms using classical image processing techniques and CNN which can learn global context. We also discuss how sun glare detection algorithm will efficiently fit into a typical automated driving system. As there is no public dataset, we created our own and will release it publicly via theWoodScape project [1] to encourage further research in this area.

Three-Dimensional Structure of Rotavirus-Fab Complex

1990 ◽  
Vol 48 (1) ◽  
pp. 238-239
Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu
Keyword(s):  
Image Processing ◽  
Smooth Surface ◽  
Three Dimensional ◽  
Outer Shell ◽  
Dimensional Structure ◽  
Structural Studies ◽  
Cell Penetration ◽  
Electron Cryomicroscopy ◽  
Image Processing Techniques ◽  
Processing Techniques

Rotaviruses are spherical, double-shelled particles. They have been identified as a major cause of infantile gastroenteritis worldwide. In our earlier studies we determined the three-dimensional structures of double-and single-shelled simian rotavirus embedded in vitreous ice using electron cryomicroscopy and image processing techniques to a resolution of 40Å. A distinctive feature of the rotavirus structure is the presence of 132 large channels spanning across both the shells at all 5- and 6-coordinated positions of a T=13ℓ icosahedral lattice. The outer shell has 60 spikes emanating from its relatively smooth surface. The inner shell, in contrast, exhibits a bristly surface made of 260 morphological units at all local and strict 3-fold axes (Fig.l).The outer shell of rotavirus is made up of two proteins, VP4 and VP7. VP7, a glycoprotein and a neutralization antigen, is the major component. VP4 has been implicated in several important functions such as cell penetration, hemagglutination, neutralization and virulence. From our earlier studies we had proposed that the spikes correspond to VP4 and the rest of the surface is composed of VP7. Our recent structural studies, using the same techniques, with monoclonal antibodies specific to VP4 have established that surface spikes are made up of VP4.

A Survey on Detection and Classification of Brain Tumor Using Image Processing Techniques

2020 ◽  
pp. 967-973
Author(s):  
V. Deepika ◽  
T. Rajasenbagam
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Soft Tissues ◽  
Tumor Detection ◽  
Tumor Classification ◽  
Normal Brain ◽  
Image Processing Techniques ◽  
Normal Brain Function ◽  
Processing Techniques ◽  
The Brain

A brain tumor is an uncontrolled growth of abnormal brain tissue that can interfere with normal brain function. Although various methods have been developed for brain tumor classification, tumor detection and multiclass classification remain challenging due to the complex characteristics of the brain tumor. Brain tumor detection and classification are one of the most challenging and time-consuming tasks in the processing of medical images. MRI (Magnetic Resonance Imaging) is a visual imaging technique, which provides a information about the soft tissues of the human body, which helps identify the brain tumor. Proper diagnosis can prevent a patient's health to some extent. This paper presents a review of various detection and classification methods for brain tumor classification using image processing techniques.

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