scholarly journals Performance Analysis of Target Information Recognition System for Agricultural Robots

2021 ◽  
Vol 12 (2) ◽  
pp. 49-60
Author(s):  
Yun Ji ◽  
Rajeev Kumar ◽  
Daljeet Singh ◽  
Maninder Singh
Keyword(s):  
Decision Making ◽  
Production Efficiency ◽  
Vision System ◽  
Recognition Rate ◽  
Robot Vision ◽  
Recognition System ◽  
Economic Benefits ◽  
Prototype System ◽  
Target Information ◽  
Information Recognition

In this paper, an agricultural robot vision system is proposed for two typical environments—farmland and orchard—combined with weeding between crops. The system includes orchard production monitoring and prediction tasks, the target information recognition approach, and visual servo decision making. The results obtained from the proposed system show that using the region combination features of image 2D histogram as the decision-making basis, the accurate and rapid indirect identification and positioning of crop seedlings can be accomplished while skipping the complex process of accurately identifying crops and weeds. The algorithm performs reasonably good as the time of target recognition in the prototype system is found to be less than 16 ms, and the average accurate recognition rate of 97.43% is achieved. The benefits of the proposed system are the continuous improvement of the quality of agricultural products, the rise of production efficiency, and the increase of economic benefits.

scholarly journals 3D Robot Vision System through 2D Shape Based Matching Using Gaussian Smoothing for Gluing Application

2018 ◽  
Vol 7 (4.33) ◽  
pp. 487
Author(s):  
Mohamad Haniff Harun ◽  
Mohd Shahrieel Mohd Aras ◽  
Mohd Firdaus Mohd Ab Halim ◽  
Khalil Azha Mohd Annuar ◽  
Arman Hadi Azahar ◽  
...  
Keyword(s):  
Template Matching ◽  
Shape Matching ◽  
Vision System ◽  
Recognition Rate ◽  
Three Dimensional ◽  
Robot Vision ◽  
Region Of Interest ◽  
Gaussian Smoothing ◽  
Detection Approach ◽  
Vision Algorithm

This investigation is solely on the adaptation of a vision system algorithm to classify the processes to regulate the decision making related to the tasks and defect’s recognition. These idea stresses on the new method on vision algorithm which is focusing on the shape matching properties to classify defects occur on the product. The problem faced before that the system required to process broad data acquired from the object caused the time and efficiency slightly decrease. The propose defect detection approach combine with Region of Interest, Gaussian smoothing, Correlation and Template Matching are introduced. This application provides high computational savings and results in better recognition rate about 95.14%. The defects occur provides with information of the height which corresponds by the z-coordinate, length which corresponds by the y-coordinate and width which corresponds by the x-coordinate. This data gathered from the proposed system using dual camera for executing the three dimensional transformation.  

A Study of Different Methodologies Helpful in the Identification of Offline Handwritten Script

2018 ◽  
Vol 6 (6) ◽  
pp. 307
Author(s):  
Manish M. Kayasth ◽  
Bharat C. Patel
Keyword(s):  
Feature Extraction ◽  
Character Recognition ◽  
Recognition Rate ◽  
Recognition System ◽  
Post Processing ◽  
Classification Technique ◽  
Scanned Image ◽  
Gujarati Language ◽  
High Degree ◽  
Selection Of

The entire character recognition system is logically characterized into different sections like Scanning, Pre-processing, Classification, Processing, and Post-processing. In the targeted system, the scanned image is first passed through pre-processing modules then feature extraction, classification in order to achieve a high recognition rate. This paper describes mainly on Feature extraction and Classification technique. These are the methodologies which play an important role to identify offline handwritten characters specifically in Gujarati language. Feature extraction provides methods with the help of which characters can identify uniquely and with high degree of accuracy. Feature extraction helps to find the shape contained in the pattern. Several techniques are available for feature extraction and classification, however the selection of an appropriate technique based on its input decides the degree of accuracy of recognition. 

GESTURE RECOGNITION SYSTEM FOR NIGERIAN TRIBAL GREETING POSTURES USING SUPPORT VECTOR MACHINE

2020 ◽  
Vol 5 (2) ◽  
pp. 609
Author(s):  
Segun Aina ◽  
Kofoworola V. Sholesi ◽  
Aderonke R. Lawal ◽  
Samuel D. Okegbile ◽  
Adeniran I. Oluwaranti
Keyword(s):  
Support Vector Machine ◽  
Gesture Recognition ◽  
Recognition Rate ◽  
Recognition Task ◽  
Recognition System ◽  
Human Interaction ◽  
Support Vector ◽  
System A ◽  
Extraction Algorithm ◽  
Gaussian Blur

This paper presents the application of Gaussian blur filters and Support Vector Machine (SVM) techniques for greeting recognition among the Yoruba tribe of Nigeria. Existing efforts have considered different recognition gestures. However, tribal greeting postures or gestures recognition for the Nigerian geographical space has not been studied before. Some cultural gestures are not correctly identified by people of the same tribe, not to mention other people from different tribes, thereby posing a challenge of misinterpretation of meaning. Also, some cultural gestures are unknown to most people outside a tribe, which could also hinder human interaction; hence there is a need to automate the recognition of Nigerian tribal greeting gestures. This work hence develops a Gaussian Blur – SVM based system capable of recognizing the Yoruba tribe greeting postures for men and women. Videos of individuals performing various greeting gestures were collected and processed into image frames. The images were resized and a Gaussian blur filter was used to remove noise from them. This research used a moment-based feature extraction algorithm to extract shape features that were passed as input to SVM. SVM is exploited and trained to perform the greeting gesture recognition task to recognize two Nigerian tribe greeting postures. To confirm the robustness of the system, 20%, 25% and 30% of the dataset acquired from the preprocessed images were used to test the system. A recognition rate of 94% could be achieved when SVM is used, as shown by the result which invariably proves that the proposed method is efficient.

OPTIMAL ANALYSIS OF FARM AGRICULTURAL MACHINERY EQUIPMENT BASED ON MATHEMATICAL MODELLING

2020 ◽  
pp. 333-340
Keyword(s):  
Mathematical Modelling ◽  
Production Efficiency ◽  
Programming Model ◽  
Constraint Equation ◽  
Economic Benefits ◽  
Agricultural Machinery ◽  
Optimization Analysis ◽  
Agricultural Modernization ◽  
Actual Equipment ◽  
Optimal Allocations

With the development of science and technology, the degree of agricultural mechanization is getting higher and higher. Agricultural machinery is an important support for the development of agricultural modernization. Optimizing the allocation of agricultural machinery is conducive to improving agricultural production efficiency and economic benefits. In this paper, mathematical modelling method is mainly used in the analysis and optimization of agricultural machinery configuration. By determining the objective function and constraint equation, combined with the actual situation of Xinjiang Production and Construction Corps, the linear programming model and workload model of agricultural machinery and equipment optimization are established. Finally, the actual number of agricultural machinery and equipment and the number of optimal allocations of Xinjiang Production and Construction Corps farm were compared. The effectiveness of the optimization model is verified by comparing the optimized agricultural machinery equipment with the actual equipment. The results show that the optimized equipment model has good optimization effect. On the basis of reducing the number of agricultural machinery and equipment, the matching rate of agricultural machinery is improved, and the operation cost of agricultural machinery is effectively reduced. It is hoped that this study can provide certain reference and reference for the optimization analysis of agricultural machinery and equipment based on mathematical modelling.

scholarly journals Industrial Robot Vision System

1983 ◽  
Vol 16 (20) ◽  
pp. 337-341
Author(s):  
V.M. Grishkin ◽  
F.M. Kulakov
Keyword(s):  
Vision System ◽  
Industrial Robot ◽  
Robot Vision

scholarly journals Application of portrait recognition system for emergency evacuation in mass emergencies

2021 ◽  
Vol 30 (1) ◽  
pp. 893-902
Author(s):  
Ke Xu
Keyword(s):  
Detection Rate ◽  
Characteristic Curve ◽  
Recognition Rate ◽  
Recognition System ◽  
Emergency Evacuation ◽  
Shopping Mall ◽  
Single Shot ◽  
Data Set ◽  
Linear Discriminant ◽  
Adaboost Algorithm

Abstract A portrait recognition system can play an important role in emergency evacuation in mass emergencies. This paper designed a portrait recognition system, analyzed the overall structure of the system and the method of image preprocessing, and used the Single Shot MultiBox Detector (SSD) algorithm for portrait detection. It also designed an improved algorithm combining principal component analysis (PCA) with linear discriminant analysis (LDA) for portrait recognition and tested the system by applying it in a shopping mall to collect and monitor the portrait and establish a data set. The results showed that the missing detection rate and false detection rate of the SSD algorithm were 0.78 and 2.89%, respectively, which were lower than those of the AdaBoost algorithm. Comparisons with PCA, LDA, and PCA + LDA algorithms demonstrated that the recognition rate of the improved PCA + LDA algorithm was the highest, which was 95.8%, the area under the receiver operating characteristic curve was the largest, and the recognition time was the shortest, which was 465 ms. The experimental results show that the improved PCA + LDA algorithm is reliable in portrait recognition and can be used for emergency evacuation in mass emergencies.

A Robot Vision System Based on Two-Dimensional Object-Oriented Models

1986 ◽  
Vol 16 (4) ◽  
pp. 582-589 ◽  
Author(s):  
Lorenz A. Schmitt ◽  
William A. Gruver ◽  
Assad Ansari
Keyword(s):  
Vision System ◽  
Robot Vision ◽  
Object Oriented ◽  
Two Dimensional ◽  
Dimensional Object

Design of Gait Recognition System Based on FPGA and DSP

2014 ◽  
Vol 687-691 ◽  
pp. 3861-3868
Author(s):  
Zheng Hong Deng ◽  
Li Tao Jiao ◽  
Li Yan Liu ◽  
Shan Shan Zhao
Keyword(s):  
Monitoring System ◽  
Nearest Neighbor ◽  
Gait Recognition ◽  
Recognition Rate ◽  
Digital Signal ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Zernike Moment ◽  
Intelligent Monitoring ◽  
The One

According to the trend of the intelligent monitoring system, on the basis of the study of gait recognition algorithm, the intelligent monitoring system is designed based on FPGA and DSP; On the one hand, FPGA’s flexibility and fast parallel processing algorithms when designing can be both used to avoid that circuit can not be modified after designed; On the other hand, the advantage of processing the digital signal of DSP is fully taken. In the feature extraction and recognition, Zernike moment is selected, at the same time the system uses the nearest neighbor classification method which is more mature and has good real-time performance. Experiments show that the system has high recognition rate.

Study of highway asphalt pavement recycling maintenance scheme decision system and decision method

2021 ◽  
pp. 1-10
Author(s):  
Hongjun Jing ◽  
Ping Yao ◽  
Lichen Song ◽  
Jiahao Zhang ◽  
Yanlong Zhao ◽  
...  
Keyword(s):  
Decision Making ◽  
Evaluation System ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Asphalt Pavement ◽  
Economic Benefits ◽  
Highway Maintenance ◽  
Decision System ◽  
Recovery Index ◽  
Pavement Recycling

With modern economic and social development, the technical and economic requirements of highway maintenance and construction projects have become increasingly complicated. Meticulous and in-depth investigation and demonstration guided by scientific theories and methods are of considerable importance to highway maintenance scheme decision. As basis for the selection of highway asphalt pavement recycling maintenance scheme, the factors influencing the decision are analytically demonstrated and an evaluation system is proposed, including three major decision indexes: applicability of recycling mode, recycled pavement quality recovery index, and economic benefit. According to the principles of data statistics and analysis, this study proposes a calculation method for the recycled pavement quality recovery index, analyzes the economic benefits of decision schemes using economic models such as recycling ratio and cost, and puts forward an optimal evaluation method of engineering cost and its fuzzy score intervals. Index weights are calculated through the analytic hierarchy process, and the comprehensive decision evaluation system and comprehensive evaluation method are established. Subsequently, the decision-making method is analyzed on the basis of the decision system by combining the related data. Results show maximum weight of the pavement quality recovery index and minor differences among four recycling schemes in the quality recovery index and applicability. The decision-making results are simplified with clear hierarchical feature because of the fuzzy score intervals of each index. Findings can provide a reference for the asphalt pavement recycling scheme decision.

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