scholarly journals Development of a dynamic intelligent recognition system for a real-time tracking robot

2021 ◽  
Vol 10 (3) ◽  
pp. 161
Author(s):  
Thair Ali Salih ◽  
Mohammed Talal Ghazal ◽  
Zaid Ghanim Mohammed
Keyword(s):  
Recognition System ◽  
Mobile Security ◽  
Light Conditions ◽  
Complex Environment ◽  
Lighting Conditions ◽  
Empirical Performance ◽  
Computer Vision Technology ◽  
Real Time Tracking ◽  
Intelligent Recognition ◽  
Pca Algorithm

<p>Nowadays, the development of computer vision technology help to overcome track and identify humans within a location in the complex environment through mobile robots, which gives the motivation to presents a vision-based approach to a mobile security robot. The proposed system utilizes a wireless camera to detect the objects in the field of robot view. Principle component analysis (PCA) algorithm and filters are used to implement and demonstrate the process of the images. This gives the designed system the ability to recognize objects independently from current light conditions. Frame tracking in the images uses an attention system to get an estimate of the position of a person. This estimate helps the applied camera to identify objects with changing background lighting conditions such as a fire inside a building. By using this estimate, the applied camera could identify objects with changing background lighting conditions such as a fire inside premises. The system has been tested using the MATLAB environment, and the empirical performance explains the efficiency and strongness of the suggested device.</p>

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.

Developing Algorithms for a Berry Recognition System Used in Robotized Harvesting of Garden Strawberry

2020 ◽  
Vol 67 (1) ◽  
pp. 133-141
Author(s):  
Dmitriy O. Khort ◽  
Aleksei I. Kutyrev ◽  
Igor G. Smirnov ◽  
Rostislav A. Filippov ◽  
Roman V. Vershinin
Keyword(s):  
Computer Vision ◽  
Technological Process ◽  
Degrees Of Freedom ◽  
Computer Control ◽  
Recognition System ◽  
Raspberry Pi ◽  
Laser Sensors ◽  
Lighting Conditions ◽  
Systems Research ◽  
Degree Of Maturity

Technological capabilities of agricultural units cannot be optimally used without extensive automation of production processes and the use of advanced computer control systems. (Research purpose) To develop an algorithm for recognizing the coordinates of the location and ripeness of garden strawberries in different lighting conditions and describe the technological process of its harvesting in field conditions using a robotic actuator mounted on a self-propelled platform. (Materials and methods) The authors have developed a self-propelled platform with an automatic actuator for harvesting garden strawberry, which includes an actuator with six degrees of freedom, a co-axial gripper, mg966r servos, a PCA9685 controller, a Logitech HD C270 computer vision camera, a single-board Raspberry Pi 3 Model B+ computer, VL53L0X laser sensors, a SZBK07 300W voltage regulator, a Hubsan X4 Pro H109S Li-polymer battery. (Results and discussion) Using the Python programming language 3.7.2, the authors have developed a control algorithm for the automatic actuator, including operations to determine the X and Y coordinates of berries, their degree of maturity, as well as to calculate the distance to berries. It has been found that the effectiveness of detecting berries, their area and boundaries with a camera and the OpenCV library at the illumination of 300 Lux reaches 94.6 percent’s. With an increase in the robotic platform speed to 1.5 kilometre per hour and at the illumination of 300 Lux, the average area of the recognized berries decreased by 9 percent’s to 95.1 square centimeter, at the illumination of 200 Lux, the area of recognized berries decreased by 17.8 percent’s to 88 square centimeter, and at the illumination of 100 Lux, the area of recognized berries decreased by 36.4 percent’s to 76 square centimeter as compared to the real area of berries. (Conclusions) The authors have provided rationale for the technological process and developed an algorithm for harvesting garden strawberry using a robotic actuator mounted on a self-propelled platform. It has been proved that lighting conditions have a significant impact on the determination of the area, boundaries and ripeness of berries using a computer vision camera.

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.

A financial ticket image intelligent recognition system based on deep learning

2021 ◽  
pp. 106955
Author(s):  
Hanning Zhang ◽  
Qinghua Zheng ◽  
Bo Dong ◽  
Boqin Feng
Keyword(s):  
Deep Learning ◽  
Recognition System ◽  
Intelligent Recognition

Intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
G. Merlin Linda ◽  
N.V.S. Sree Rathna Lakshmi ◽  
N. Senthil Murugan ◽  
Rajendra Prasad Mahapatra ◽  
V. Muthukumaran ◽  
...  
Keyword(s):  
Spatial Information ◽  
Intelligent System ◽  
Gait Recognition ◽  
Research Work ◽  
Recognition System ◽  
Multimodal Fusion ◽  
Content Type ◽  
Surveillance Videos ◽  
Sensor Devices ◽  
Intelligent Recognition

PurposeThe paper aims to introduce an intelligent recognition system for viewpoint variations of gait and speech. It proposes a convolutional neural network-based capsule network (CNN-CapsNet) model and outlining the performance of the system in recognition of gait and speech variations. The proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech variations.Design/methodology/approachThis proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNN and used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in viewpoint. The proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of CNN-CapsNet.FindingsThis research work provides recognition of signal, biometric-based gait recognition and sound/speech analysis. Empirical evaluations are conducted on three aspects of scenarios, namely fixed-view, cross-view and multi-view conditions. The main parameters for recognition of gait are speed, change in clothes, subjects walking with carrying object and intensity of light.Research limitations/implicationsThe proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.Practical implicationsThis research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.Originality/valueThis proposed research work proves to be performing better for the recognition of gait and speech when compared with other techniques.

scholarly journals Morphological features of Hylotelephium triphillum (Haw.) Holub (Crassulaceae DC.) under different light conditions when introduced into the steppe zone

2016 ◽  
Vol 5 (2) ◽  
pp. 47-51
Author(s):  
Lidiya Vasilyevna Privalko
Keyword(s):  
Fruit Set ◽  
Steppe Zone ◽  
Botanical Garden ◽  
Light Conditions ◽  
Biometric Data ◽  
Habitat Features ◽  
Lighting Conditions ◽  
Air Temperatures ◽  
Natural Flora ◽  
The Impact

In recent decades floral devices in a natural style has been becoming more common in gardening. In this connection there was a need for the introduction and study of the natural flora of plants in order to attract them to simulate the decorative and resistant plants. The article presents the results of studies of the effect of different light conditions on the habitat features and decorative biomorphological Hylotelephium triphyllum (Haw.) Holub (Crassulaceae DC.) when introduced in SE Donetsk Botanical Garden. This species is found naturally in the flora of Donbass, a decorative, but, according to the results of our analysis, is rarely used in green construction. Bioecological certification of this type has been done. It has been determined that the impact of site lighting conditions on the growth and development of H. triphyllum expressed in significantly smaller numbers of vegetative and generative shoots in the shaded areas. However, since the diameter of the plants does not change, more thickened planting in these areas is not recommended. The author found the dependence of the variation of the biometric data on the lighting conditions. In the study of seasonal dynamics of H. triphyllum the author revealed that the development of above-ground organs of his passes with a positive amount of average daily air temperatures. The growing season lasts an average of 225 days. Start of spring regrowth is observed in the second half of March - early April, flowering - in August - September, fruits - in September - October. Vegetation stops when temperature goes below zero. Illumination of this type of habitat affect the time of vegetation beginning, budding, flowering, fruit set and fruit-bearing. On the shaded areas due to the later start of budding and flowering the most decorative period of H. triphyllum is shorter by an average of 10 days. This type is recommended for creation of group planting, stony hills, dry streams, rock gardens, rockeries, mixborders, curbs, ornamental compositions in the coastal zone of ornamental ponds and fountains in the steppe zone in areas with different light conditions, taking into account the above factors.

scholarly journals An Automatic Traffic Rules Violation Detection and Number Plate Recognition System for Bangladesh

2020 ◽  
Vol 19 (2) ◽  
pp. 87-98
Author(s):  
Raian Shahrear ◽  
Md. Anisur Rahman ◽  
Atif Islam ◽  
Chamak Dey ◽  
Md. Saniat Rahman Zishan
Keyword(s):  
Neural Network ◽  
Recognition System ◽  
The Road ◽  
Controlling System ◽  
Detection And Identification ◽  
Violation Detection ◽  
Computer Vision Technology ◽  
On The Road ◽  
Day By Day ◽  
Traffic Rules

The traffic controlling system in Bangladesh has not been updated enough with respect to fast improving technology. As a result, traffic rules violation detection and identification of the vehicle has become more difficult as the number of vehicles is increasing day by day. Moreover, controlling traffic is still manual. To solve this problem, the traffic controlling system can be digitalized by a system that consists of two major parts which are traffic rules violation detection and number plate recognition. In this research, these processes are done automatically which is based on machine learning, deep learning, and computer vision technology. Before starting this process, an object on the road is identified through the YOLOv3 algorithm. By using the OpenCV algorithm, traffic rules violation is detected and the vehicle that violated these rules is identified. To recognize the number plate of the vehicle, image acquisition, edge detection, segmentation of characters is done sequentially by using Convolution Neural Network (CNN) in MATLAB background. Among the traffic rules, the following traffic signal is implemented in this research.

scholarly journals Automatic Assembly of Bolts and Nuts Based on Machine Vision Recognition

2021 ◽  
Vol 2113 (1) ◽  
pp. 012033
Author(s):  
Haocheng He
Keyword(s):  
Computer Vision ◽  
Production Line ◽  
Recognition System ◽  
Automatic Assembly ◽  
Robot Arm ◽  
Accuracy Improvement ◽  
Automatic Production ◽  
Computer Vision Technology ◽  
Automatic Production Line ◽  
Pixel Scale

Abstract In this study, based on the computer vision technology, we developed a recognition system for nuts positioning to complete the automatic bolt assembly part of the automatic production line. The actual image of the nut was captured by an industrial camera, which would be processed by the following edge detection and Hough circle transformation. After that, the coordinates of the nuts were obtained in the pixel scale. Finally, the real position of nuts would be fed back to the robot arm, according to which the automatic assembly of the bolt would be completed. This computer vision based recognition system is an indispensable part for the efficiency and accuracy improvement of automatic production line.

A simple microcomputer-based system for real-time analysis of cell behaviour

1987 ◽  
Vol 87 (1) ◽  
pp. 171-182
Author(s):  
J.A. Dow ◽  
J.M. Lackie ◽  
K.V. Crocket
Keyword(s):  
Real Time ◽  
Search Algorithm ◽  
Cell Types ◽  
Real Time Analysis ◽  
Lighting Conditions ◽  
Previous Frame ◽  
Real Time Tracking ◽  
Cell Densities ◽  
Different Cell Types

An image analysis package based on a BBC microcomputer has been developed, which can simultaneously track many moving cells in vitro. Cells (rabbit neutrophil leucocytes, BHK C13 fibroblasts, or PC12 phaeochromocytoma cells) are viewed under phase optics with a monochrome TV camera, and the signal digitized. Successive frames are acquired by the computer as a 640 X 256 pixel array. Under controlled lighting conditions, cells can readily be isolated from the background by binary filtering. In real-time tracking, the positions of a given cell in successive frames are obtained by searching the area around the cell's centroid in the previous frame. A simple box-search algorithm is described, which proves highly successful at low cell densities. The resilience of different search algorithms to various exceptional conditions (such as collisions) is discussed. The success of this system in real-time tracking is largely dependent upon the leisurely speed of movement of cells, and on obtaining a clean, high quality optical image to analyse. The limitations of this technique for different cell types, and the possible configurations of more sophisticated hardware, are outlined. This system provides a versatile and automated solution to the problem of studying the movement of tissue cells.

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