scholarly journals RECOGNITION METHOD OF ELLIPTIC FORMS OBJECTS ON THE IMAGES

2019 ◽  
Vol 2019 (3) ◽  
pp. 4-8
Author(s):  
Евгений Леонов ◽  
Evgeny Leonov ◽  
Юрий Леонов ◽  
Yuriy Leonov ◽  
Андрей Аверченков ◽  
...  
Keyword(s):  
Mobile Devices ◽  
High Speed ◽  
Video Camera ◽  
Recognition System ◽  
Recognition Method ◽  
Computing Power ◽  
The Road ◽  
Road Signs ◽  
Recognition Systems ◽  
Intelligent Recognition

The article briefly describes the methodology and suggests the method for recognizing any elliptic forms objects on the images. This method is universal and can be applied in any intelligent recognition systems, for example, recognition system of the road signs from video camera images. The proposed method has proven itself in solving various practical problems, such as searching for signs in photographs, detecting circles on charts and diagrams, searching for the boundaries of ovals of faces, etc. The main advantage of the method is its extreme ease of implementation and high speed, which makes it possible to use not only on modern stationary computers, but also on mobile devices with low computing power.

scholarly journals Application on character recognition system on road sign for visually impaired: case study approach and future

2020 ◽  
Vol 10 (1) ◽  
pp. 778
Author(s):  
Jaejoon Kim
Keyword(s):  
Phase I ◽  
Visual Information ◽  
Character Recognition ◽  
Visually Impaired ◽  
Recognition System ◽  
The Road ◽  
Road Signs ◽  
Road Sign ◽  
Text Information ◽  
On The Road

Many visually impaired people worldwide are unable to travel safely and autonomously because they are physically unable to perceive effective visual information during their daily lives. In this research, we study how to extract the character information of the road sign and transmit it to the visually impaired effectively, so they can understand easier. Experimental method is to apply the Maximally Stable External Region and Stroke Width Transform method in Phase I so that the visually impaired person can recognize the letters on the road signs. It is to convey text information to the disabled. The result of Phase I using samples of simple road signs was to extract the sign information after dividing the exact character area, but the accuracy was not good for the Hangul (Korean characters) information. The initial experimental results in the Phase II succeeded in transmitting the text information on Phase I to the visually impaired. In the future, it will be required to develop a wearable character recognition system that can be attached to the visually impaired. In order to perform this task, we need to develop and verify a miniaturized and wearable character recognition system. In this paper, we examined the method of recognizing road sign characters on the road and presented a possibility that may be applicable to our final development.

OBJECT RECOGNITION SYSTEM ON THE ROAD

2016 ◽  
Vol 3 (1) ◽  
pp. 224-227
Author(s):  
Жданова ◽  
O. Zhdanova ◽  
Макарова ◽  
I. Makarova
Keyword(s):  
Object Recognition ◽  
General Scheme ◽  
Recognition System ◽  
The Road ◽  
Advantages And Disadvantages ◽  
Recognition Systems ◽  
On The Road ◽  
Objects Detection ◽  
Detection And Recognition

This article outlines the existing safety problems on the road, describes the existing recognition systems of well-known automobile manufacturers, and considers advantages and disadvantages of existing solutions. The general scheme of solving the problem of objects detection and recognition was showed.

scholarly journals A Research Paper on Convolutional Neural Network (CNN) Theory based Automated Traffic and Road Sign Detection and Recognition System

2021 ◽  
Vol 9 (VII) ◽  
pp. 3775-3783
Author(s):  
Parkavi J.
Keyword(s):  
Road Safety ◽  
Road Network ◽  
Good Accuracy ◽  
Recognition System ◽  
Accuracy Rate ◽  
Traffic System ◽  
The Road ◽  
Road Signs ◽  
Road Sign ◽  
Sign Detection

India is a country with a dense road network and has a complex system to maintain road safety. As we all know that we have a complex traffic system in which we have more than 100 types of traffic symbols in it. While driving, it is tough to take care of all the symbols placed at the road end. Sometimes the driver does not know what that symbol says. In this system sometimes the driver misses the road signs because the attention of the driver is overdriving the vehicle safe which leads to an accident or issuing Challan. Sometimes the traffic signs don't notice by the driver. So all the drivers or the vehicle need a system which is capable to read and recognize the traffic symbol placed at the road end and the system must be capable of giving simple instruction to the driver. So that system can automatically detect which type of symbol is this and can notify the driver. The system must have a good accuracy rate, as well as the system, must have a very good speed of working. This system can also be used in driverless cars to notify the system about the road signals and hence the system can tackle all the symbols carefully.

COLOR IMAGE SEGMENTATION WITH SUPPORT VECTOR MACHINES: APPLICATIONS TO ROAD SIGNS DETECTION

2008 ◽  
Vol 18 (04) ◽  
pp. 339-345 ◽  
Author(s):  
BOGUSŁAW CYGANEK
Keyword(s):  
Input Data ◽  
Color Image ◽  
Feature Space ◽  
Recognition System ◽  
Color Image Segmentation ◽  
Support Vector ◽  
The Road ◽  
Road Signs ◽  
Higher Dimensional ◽  
Vector Machines

In this paper we propose efficient color segmentation method which is based on the Support Vector Machine classifier operating in a one-class mode. The method has been developed especially for the road signs recognition system, although it can be used in other applications. The main advantage of the proposed method comes from the fact that the segmentation of characteristic colors is performed not in the original but in the higher dimensional feature space. By this a better data encapsulation with a linear hypersphere can be usually achieved. Moreover, the classifier does not try to capture the whole distribution of the input data which is often difficult to achieve. Instead, the characteristic data samples, called support vectors, are selected which allow construction of the tightest hypersphere that encloses majority of the input data. Then classification of a test data simply consists in a measurement of its distance to a centre of the found hypersphere. The experimental results show high accuracy and speed of the proposed method.

Research on Road Target Recognition Method Based on Optical Image

2014 ◽  
Vol 602-605 ◽  
pp. 1968-1971
Author(s):  
Man Zhao ◽  
Jin Jiang Cui ◽  
Fei Guo ◽  
Mei Zhao ◽  
Da Yong Jiang
Keyword(s):  
Target Recognition ◽  
Recognition System ◽  
Optical Image ◽  
Recognition Method ◽  
C Language ◽  
The Road ◽  
Optical Images ◽  
Target Extraction ◽  
Very High ◽  
Detection And Recognition

With the development of science and technology, optical images with very high resolution have been able to provide a large amount of information. Therein the road target is the most widely used in optical image. Road target detection and recognition is extremely important for reducing a lot of practical work and greatly improving the efficiency of the target extraction and identification. Aimed at this problem, we propose a road target recognition method based on optical image.The method is realized by joining human recognize and identify, combining with the intelligence of computer processing and powerful place. So in this work, the method based on edge detection and Hough transform algorithm is exploded. The man-machine interactive recognition system (Road Target Extraction and Recognition System) is developed. The system is realized under Windows operating system. The tool is Visual C++ 6.0 software. The platform is MFC functions. The system is written in C++ language. The characteristics of the system are the strong pertinence and the simple operation. When the system is applied safely, the results are definite and clear.

Experimental Evaluation of the Pitch Angle Righting Capabilities of a High Speed Terrestrial Vehicle in Ballistic Phase

2012 ◽  
Vol 162 ◽  
pp. 57-66 ◽  
Author(s):  
Marc Davis ◽  
Philippe Vaslin ◽  
Jean Christophe Fauroux ◽  
Christophe Gouinaud ◽  
Liang Ju
Keyword(s):  
Pitch Angle ◽  
High Speed ◽  
Video Camera ◽  
Automated Control ◽  
Ground Vehicle ◽  
The Road ◽  
High Speed Video ◽  
High Speed Video Camera ◽  
Angular Velocities ◽  
The Relationship

We present a study of the feasibility of controlling the pitch angle of a high velocity ground vehicle in ballistic phase by accelerating or decelerating its wheels. The vehicle performed several jumps, and various wheel acceleration commands were sent to it while it was airborne. Images were recorded using a high-speed video camera, and the trajectories of markers placed on the vehicle were analyzed in order to measure the relationship between the changes in angular velocities of the chassis and the wheels. It appeared that it was possible to achieve pitch righting through the modification of the angular velocities of the wheels with adequate performance, thus opening the road towards automated control of pitch, then later yaw and roll angles.

scholarly journals Hand Recognition Using Thermal Image and Extension Neural Network

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Meng-Hui Wang
Keyword(s):  
Neural Network ◽  
Infrared Camera ◽  
Recognition System ◽  
Thermal Image ◽  
Recognition Method ◽  
Good Tolerance ◽  
Personal Recognition ◽  
Recognition Systems ◽  
Hand Recognition ◽  
High Degree

Hand recognition is one of the popular biometry methods for access control systems. In this paper, a new scheme for personal recognition using thermal images of the hand and an extension neural network (ENN) is presented. The features of the recognition system are extracted from gray level hand images, which are taken by an infrared camera. The main advantage of the thermal image is that it can reduce errors and noise in the features extracted stage, which is most important to increase the accuracy of recognition systems. Moreover, a new recognition method based on the ENN is proposed to perform the core functions of the hand recognition system. The proposed ENN-based recognition method also permits rapid adaptive processing for a new pattern, as it only tunes the boundaries of classified features or adds a new neural node. It is feasible to implement the proposed method on a Microcomputer for a portable personal recognition device. From the tested examples, the proposed method has a significantly high degree of recognition accuracy and shows good tolerance to errors added.

scholarly journals Modification of the Pre-Processing Stage of a Traffi Sign Recognition System Taking into Account the Characteristics of the Subject Area

Vestnik NSUEM ◽  
2020 ◽  
pp. 235-249
Author(s):  
S. Yu. Pchelintsev
Keyword(s):  
Processing Speed ◽  
Recognition System ◽  
Subject Area ◽  
Traffic Sign Recognition ◽  
Traffic Sign ◽  
Road Signs ◽  
Sign Recognition ◽  
The Subject ◽  
Recognition Systems ◽  
High Level

Traffic sign recognition systems require a high level of responsiveness and accuracy with limited use of computing resources. The process of image pre-processing precedes the process of directly recognizing images, therefore, the recognition results depend on its effectiveness. When conducting pre-processing, it is important to take into account the features of the subject area, within which recognition is performed. The article discusses the process of pre-processing and preparing images in the context of creating a system for recognizing road signs. The main problems that arise during the operation of such a system are identified. Their solutions are proposed. Own combination of these solutions allowed us to create a new system for recognizing road signs, which gives a gain in processing speed by cutting off images of no interest before entering the classifier, and also taking into account the peculiarities of operation in an urban environment – more difficult conditions compared with recognition of road signs on tracks or on artificially created training grounds.

Human Ear Pattern Recognition System

2017 ◽  
Vol 7 (8) ◽  
pp. 117 ◽  
Author(s):  
V. Jagan Naveen ◽  
K. Krishna Kishore ◽  
P. Rajesh Kumar
Keyword(s):  
Pattern Recognition ◽  
Expectation Maximization Algorithm ◽  
Recognition System ◽  
Modern World ◽  
Person Identification ◽  
Biometric Systems ◽  
Different Types ◽  
Recognition Systems ◽  
Human Ear ◽  
Pca Algorithm

In the modern world, human recognition systems play an important role to   improve security by reducing chances of evasion. Human ear is used for person identification .In the Empirical study on research on human ear, 10000 images are taken to find the uniqueness of the ear. Ear based system is one of the few biometric systems which can provides stable characteristics over the age. In this paper, ear images are taken from mathematical analysis of images (AMI) ear data base and the analysis is done on ear pattern recognition based on the Expectation maximization algorithm and k means algorithm.  Pattern of ears affected with different types of noises are recognized based on Principle component analysis (PCA) algorithm.

Research on visual recognition intelligent system of city brand image based on fuzzy theory and regional culture

2021 ◽  
pp. 1-9
Author(s):  
Lin Han ◽  
Lu Han
Keyword(s):  
Neural Network ◽  
Visual Recognition ◽  
Intelligent System ◽  
Brand Image ◽  
Fuzzy Theory ◽  
Recognition System ◽  
Market Competitiveness ◽  
Visual Identity ◽  
Fuzzy Neural ◽  
Intelligent Recognition

With the rapid development of China’s market economy, brand image is becoming more and more important for an enterprise to enhance its market competitiveness and occupy a favorable market share. However, the brand image of many established companies gradually loses with the development of society and the improvement of people’s aesthetic pursuit. This has forced it to change its corporate brand image and regain the favor of the market. Based on this, this article combines the related knowledge and concepts of fuzzy theory, from the perspective of visual identity design, explores the development of corporate brand image visual identity intelligent system, and aims to design a set of visual identity system that is different from competitors in order to shape the enterprise. Distinctive brand image and improve its market competitiveness. This article first collected a large amount of information through the literature investigation method, and made a systematic and comprehensive introduction to fuzzy theory, visual recognition technology and related theoretical concepts of brand image, which laid a sufficient theoretical foundation for the later discussion of the application of fuzzy theory in the design of brand image visual recognition intelligent system; then the fuzzy theory algorithm is described in detail, a fuzzy neural network is proposed and applied to the design of the brand image visual recognition intelligent system, and the design experiment of the intelligent recognition system is carried out; finally, through the use of the specific case of KFC brand logo, the designed intelligent recognition system was tested, and it was found that the visual recognition intelligent system had an overall accuracy rate of 96.08% for the KFC brand logo. Among them, the accuracy rate of color recognition was the highest, 96.62%; comparing the changes in the output value of the training sample and the test sample, the output convergence effect of the color network is the best; through the comparison test of the BP neural network, the recognition effect of the fuzzy neural network is better.

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