A study of pupil detection and tracking by image processing techniques for a human eye-computer interaction system

Author(s):  
Ryo Shimata ◽  
Yoshihiro Mitani ◽  
Tsumoru Ochiai
2019 ◽  
Vol 3 (2) ◽  
pp. 140
Author(s):  
Yona Fransiska Dewi ◽  
Nurul Fadillah

The various knowledge and techniques of digital image processing currently available vary greatly. Research and development has been carried out towards object detection and tracking. Color is one of the parameters used to detect and track objects. Humans can distinguish a color, but a computer may not necessarily recognize that color. Digital image processing techniques that can recognize colors, one of which is color filtering. In this study, Color filtering is a technique of processing digital images based on specific colors, detecting and tracking colors by using a web camera (webcam) and red objects. Object Tracking is the process of following an object that moves and moves position, so that the colored object being tracked will draw in realtime with the results of the colors that can be selected.


Author(s):  
Hesham Ismail ◽  
Mohammed Alhussein ◽  
Nawal Aljasmi ◽  
Saeed Almazrouei

Abstract Solar energy is getting a lot of traction due to the reduced cost and friendlier to the environment compared to fossil fuel. It is essential to inspect the PV farms to ensure that the correct capacity produced through early PV fault detection. We proposed a full autonomous solution, where the drone mission is programmed to follow a specific Global Positioning System (GPS) waypoints. The collected videos will undergo various image processing techniques to detect and track the PV panels. In this paper, we tried two different PV panel detection approaches. Both detections gave acceptable results. The first detection relies on various image processing techniques. The second detection relies on deep learning architecture called mask Region-based Convolution Neural Network (R-CNN). After that, we track the PV panels in every frame using camera data alone. The advantage of tracking the PV panels is to ensure unrepeated PV panel through tagging even if the drone flies over the panel again since each PV panel will be associated with a tag. The next step will be to test the PV panel’s proposed detection and tracking algorithm on a larger solar farm.


2019 ◽  
Vol 1215 ◽  
pp. 012021 ◽  
Author(s):  
Guoshuai Li ◽  
Muhammed Burak Agir ◽  
Konstantinos Kontis ◽  
Takahiro Ukai ◽  
Sriram Rengarajan

Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu

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.


Author(s):  
V. Deepika ◽  
T. Rajasenbagam

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.


2019 ◽  
Vol 7 (5) ◽  
pp. 165-168 ◽  
Author(s):  
Prabira Kumar Sethy ◽  
Swaraj Kumar Sahu ◽  
Nalini Kanta Barpanda ◽  
Amiya Kumar Rath

2018 ◽  
Vol 6 (6) ◽  
pp. 1493-1499
Author(s):  
Shrutika.C.Rampure . ◽  
Dr. Vindhya .P. Malagi ◽  
Dr. Ramesh Babu D.R

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