Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

scholarly journals Multimedia Image Processing Lab Experiment/Simulation

2020 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Md Mamunur Rashid
Keyword(s):  
Image Processing ◽  
Video Compression ◽  
Video Processing ◽  
Multimedia Systems ◽  
Multimedia System ◽  
Image And Video Processing ◽  
Indexing And Retrieval ◽  
Video Indexing And Retrieval ◽  
Multimedia Image ◽  
Processing Techniques

Image Processing in Multimedia Applications treats a number of critical topics in multimedia systems, with respect to image and video processing techniques and their implementations. These techniques include the Image and video compression techniques and standards, and Image and video indexing and retrieval techniques. Image Processing is an important tool to develop a Multimedia system design.

Vehicle Security Distance Control Based on Binocular Parallax Vision

2014 ◽  
Vol 644-650 ◽  
pp. 207-210
Author(s):  
Shuang Liu ◽  
Xiang Jie Kong ◽  
Ming Cai Shan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
High Precision ◽  
Stereo Matching ◽  
Vision System ◽  
Intelligent Transportation ◽  
Distance Control ◽  
Calibration Methods ◽  
Computer Vision Technology ◽  
Vehicle Security

Binocular parallax vision system is a kind of computer vision technology. Two cameras on different locations can get two different pictures of same object. The space position of the object can be calculated by the parallax information of two different pictures. The binocular parallax vision technology includes cameras calibration, image processing, and stereo matching analysis. The paper will introduce the inside and outside parameters calibration methods, and combing the traffic applications, designed the calibrating scheme. The parameters that obtained according to the scheme can meet the demands of measuring the vehicle distance. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.

Sixth Sense Technology

2016 ◽  
pp. 188-215 ◽  
Author(s):  
Zeenat S. AlKassim ◽  
Nader Mohamed
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Human Computer Interaction ◽  
Gesture Recognition ◽  
Real World ◽  
Digital World ◽  
The Future ◽  
Computer Interaction

In this chapter, the authors discuss a unique technology known as the Sixth Sense Technology, highlighting the future opportunities of such technology in integrating the digital world with the real world. Challenges in implementing such technologies are also discussed along with a review of the different possible implementation approaches. This review is performed by exploring the different inventions in areas similar to the Sixth Sense Technology, namely augmented reality (AR), computer vision, image processing, gesture recognition, and artificial intelligence and then categorizing and comparing between them. Lastly, recommendations are discussed for improving such a unique technology that has the potential to create a new trend in human-computer interaction (HCI) in the coming years.

A SURVEY OF BIOLOGICALLY INSPIRED IMAGE PROCESSING FOR OBJECTS RECOGNITION

2009 ◽  
Vol 09 (04) ◽  
pp. 495-510 ◽  
Author(s):  
WEIREN SHI ◽  
ZUOJIN LI ◽  
XIN SHI ◽  
ZHI ZHONG
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Vision System ◽  
Human Vision ◽  
Image Perception ◽  
Biologically Inspired ◽  
Recognition Mechanism ◽  
Environmental Objects ◽  
Future Work ◽  
Animal Vision

The human vision system is a very sophisticated image processing and objects recognition mechanism. However, it is a challenge to simulate the human or animal vision system to automate visual function in machines, because it is difficult to account for the view-invariant perception of universals such as environmental objects or processes and the explicit perception of featural parts and wholes in visual scenes. In this paper, we first present an introduction to the importance of biologically inspired computer vision and review general and key vision functions from neuroscience perspective. And most significantly, we give an important summarization to and discussion on the specific applications of biologically inspired modeling, including biologically inspired image pre-processing, image perception, and objects recognition. In the end, we give some important and challenging topics of computer vision for future work.

scholarly journals Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform

2013 ◽  
Vol 15 (1) ◽  
pp. 80-94 ◽  
Author(s):  
S. Cubero ◽  
N. Aleixos ◽  
F. Albert ◽  
A. Torregrosa ◽  
C. Ortiz ◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Citrus Fruit ◽  
Mobile Platform ◽  
Computer Vision System

scholarly journals Fenômica

2020 ◽  
Vol 11 (1) ◽  
pp. 1-22
Author(s):  
Marcos Roberto dos Santos ◽  
Guilherme Afonso Madalozzo ◽  
José Maurício Cunha Fernandes ◽  
Rafael Rieder
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Web Application ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Research ◽  
Vision System ◽  
Low Cost ◽  
Wheat Crop ◽  
Three Solutions

Computer vision and image processing procedures could obtain crop data frequently and precisely, such as vegetation indexes, and correlating them with other variables, like biomass and crop yield. This work presents the development of a computer vision system for high-throughput phenotyping, considering three solutions: an image capture software linked to a low-cost appliance; an image-processing program for feature extraction; and a web application for results' presentation. As a case study, we used normalized difference vegetation index (NDVI) data from a wheat crop experiment of the Brazilian Agricultural Research Corporation. Regression analysis showed that NDVI explains 98.9, 92.8, and 88.2% of the variability found in the biomass values for crop plots with 82, 150, and 200 kg of N ha1 fertilizer applications, respectively. As a result, NDVI generated by our system presented a strong correlation with the biomass, showing a way to specify a new yield prediction model from the beginning of the crop.

Computer Vision and Pattern Recognition in Forensic Science

2019 ◽  
pp. 66-74
Author(s):  
Dmitrii Bakhteev
Keyword(s):  
Neural Network ◽  
Computer Vision ◽  
Vision System ◽  
Modern Technology ◽  
Training Dataset ◽  
Network Training ◽  
Application Systems ◽  
Current State ◽  
History Of ◽  
Artificial Neural

The article discusses computer vision as a modern technology of automatic processing of graphic images, analyzes the relations between the terms «computer vision» and «machine vision». History of development of this technology is described, it occurred because of improvements in both computer technology and software. The computerization of forensic activities boils down to three areas: speeding up, simplifying, and improving the efficiency of information processing. A schema of a typical computer vision system is given, the possibility of using systems based on artificial neural networks for image analysis is considered. The current state of computer vision application systems and the possibility of its application in order to solve the problems of criminal justice are analyzed. The main areas of application of computer vision in forensic activities are identification of a person on the basis of his appearance, both during operational identification of a person and portrait examinations, photo and video examinations; quantitative assessment of objects in the image (for example, in case of calculating mass events’ participants); at preliminary and expert research of documents and their requisites; in functioning of criminal registration systems. Criteria and technical conditions for sampling signatures for creation of a training dataset for a neural network are given, the basics of developing an artificial neural network recognizing signs of signatures’ forgery is analyzed, which include three steps: creating a training dataset, adjusting weights and training priorities, testing the quality of network training.

Face Detection and Recognition Using OpenCV

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Ramadan TH. Hasan ◽  
◽  
Amira Bibo Sallow ◽  
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Facial Expressions ◽  
Face Detection ◽  
Video Processing ◽  
Recognition Of Facial Expressions ◽  
Image And Video Processing ◽  
Gender And Age ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Intel's OpenCV is a free and open-access image and video processing library. It is linked to computer vision, like feature and object recognition and machine learning. This paper presents the main OpenCV modules, features, and OpenCV based on Python. The paper also presents common OpenCV applications and classifiers used in these applications like image processing, face detection, face recognition, and object detection. Finally, we discuss some literary reviews of OpenCV applications in the fields of computer vision such as face detection and recognition, or recognition of facial expressions such as sadness, anger, happiness, or recognition of the gender and age of a person.

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