scholarly journals Illumination-invariant vegetation detection for a vision sensor-based agricultural applications

2021 ◽  
Vol 11 (2) ◽  
pp. 1284
Author(s):  
Keun Ha Choi ◽  
SooHyun Kim
Keyword(s):  
Spectral Properties ◽  
Weather Conditions ◽  
High Accuracy ◽  
Vision Sensor ◽  
Illumination Invariant ◽  
Autonomous Machines ◽  
Agricultural Applications ◽  
Novel Method ◽  
Computational Simplicity ◽  
Scene Illumination

In this paper, we propose a novel method, illumination-invariant vegetation detection (IVD), to improve many aspects of agriculture for vision-based autonomous machines or robots. The proposed method derives new color feature functions from simultaneously modeling the spectral properties of the color camera and scene illumination. An experiment in which an image sample dataset was acquired under nature illumination, including various intensities, weather conditions, shadows and reflections, was performed. The results show that the proposed method (IVD) yields the highest performance with the lowest error and standard deviation and is superior to six typical methods. Our method has multiple strengths, including computational simplicity and uniformly high-accuracy image segmentation.

The questions of methodology of field experiments in agriculture and crop production

2018 ◽  
Vol 1 (94) ◽  
pp. 38-44
Author(s):  
А.M. Malienkо ◽  
N.E. Borуs ◽  
N.G. Buslaeva
Keyword(s):  
Labor Productivity ◽  
Crop Production ◽  
Field Experiments ◽  
Weather Conditions ◽  
High Accuracy ◽  
Experimental Plot ◽  
Increase Labor Productivity ◽  
Biometric Parameters ◽  
Field Crops ◽  
High Condition

In the article, the results of research on the methodology for conducting studies with corn culture under various methods of sowing and weather conditions. The aim of the research was to establish and evaluate the reliability and high accuracy of the experiment, with a decrease in the area's acreage and taking one plant per repetition. Based on the results of the analysis of biometric parameters and yields, the possibility of sampling from 5 to 108 plants was established statistically and mathematically to establish the accuracy of the experiment. The established parameters of sites in experiments with maize indicate the possibility of obtaining much more information from a smaller unit of area, that is, to increase labor productivity not only with tilled crops. This is the goal of further scientific research with other field crops taking 1 plant of repetitions, observing the conditions of leveling the experimental plot according to the fertility of the soil and sowing seeds with high condition. The data obtained give grounds for continuing research on the minimum space required and the sample in the experiments.

Measuring fiber orientations in nonwoven web images using corner detection by Bézier fitting curves

2017 ◽  
Vol 88 (18) ◽  
pp. 2120-2131 ◽  
Author(s):  
Jue Hou ◽  
Bugao Xu ◽  
Hanchao Gao ◽  
RongWu Wang
Keyword(s):  
Curve Fitting ◽  
Fiber Orientation ◽  
Euclidean Distance ◽  
High Accuracy ◽  
Corner Detection ◽  
Bézier Curve ◽  
Corner Points ◽  
Novel Method ◽  
Web Images ◽  
Orientation Statistics

This paper describes a novel method for measuring fiber orientations in nonwoven web images by using Bézier fitting curves to detect corners of fiber edges and to separate crossing fiber edges. First, the Canny detector was adopted to extract fiber edges. Second, Bézier curve fitting was used to fit each fiber edge for calculating the curvature of every point on the edge. Third, corner points were detected by locating points where the curvatures were minimal on various edges and below the threshold to divide edges into segments for orientation calculations. Last, a formula calculating the fiber orientation statistics based on the Euclidean distance was established. The experiment results demonstrated that the proposed method is robust for analyzing different nonwoven web images, and has a high accuracy for corner detection and fiber orientation calculation.

scholarly journals USING MOBILE LASER SCANNING DATA FOR FEATURES EXTRACTION OF HIGH ACCURACY DRIVING MAPS

2016 ◽  
Vol XLI-B3 ◽  
pp. 433-439 ◽  
Author(s):  
Bisheng Yang ◽  
Yuan Liu ◽  
Fuxun Liang ◽  
Zhen Dong
Keyword(s):  
Laser Scanning ◽  
Human Error ◽  
Traffic Accidents ◽  
Three Dimensional ◽  
Point Clouds ◽  
High Accuracy ◽  
3D Point Clouds ◽  
Assistant Systems ◽  
Novel Method ◽  
High Flexibility

High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

scholarly journals Service Recommendation with High Accuracy and Diversity

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shengqi Wu ◽  
Huaizhen Kou ◽  
Chao Lv ◽  
Wanli Huang ◽  
Lianyong Qi ◽  
...  
Keyword(s):  
Web Services ◽  
Web Service ◽  
Weight Vector ◽  
High Accuracy ◽  
Information Resources ◽  
Cosine Similarity ◽  
Service Recommendation ◽  
Key Factor ◽  
Novel Method

In recent years, the number of web services grows explosively. With a large amount of information resources, it is difficult for users to quickly find the services they need. Thus, the design of an effective web service recommendation method has become the key factor to satisfy the requirements of users. However, traditional recommendation methods often tend to pay more attention to the accuracy of the results but ignore the diversity, which may lead to redundancy and overfitting, thus reducing the satisfaction of users. Considering these drawbacks, a novel method called DivMTID is proposed to improve the effectiveness by achieving accurate and diversified recommendations. First, we utilize users’ historical scores of web services to explore the users’ preferences. And we use the TF-IDF algorithm to calculate the weight vector of each web service. Second, we utilize cosine similarity to calculate the similarity between candidate web services and historical web services and we also forecast the ranking scores of candidate web services. At last, a diversification method is used to generate the top- K recommended list for users. And through a case study, we show that DivMTID is an effective, accurate, and diversified web service recommendation method.

Convolutional Neural Network Considering the Effects of Noise for Bearing Fault Diagnosis

2020 ◽  
Author(s):  
Ilyoung Han ◽  
Jangbom Chai ◽  
Chanwoo Lim ◽  
Taeyun Kim
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Convolutional Neural Network ◽  
High Accuracy ◽  
Training Data ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
System Noise ◽  
Novel Method ◽  
Maintenance Activities

Abstract Convolutional Neural Network (CNN) is, in general, good at finding principal components of data. However, the characteristic components of the signals could often be obscured by system noise. Therefore, even though the CNN model is well-trained and predict with high accuracy, it may detect only the primary patterns of data which could be formed by system noise. They are, in fact, highly vulnerable to maintenance activities such as reassembly. In other words, CNN models could misdiagnose even with excellent performances. In this study, a novel method that combines the classification using CNN with the data preprocessing is proposed for bearing fault diagnosis. The proposed method is demonstrated by the following steps. First, training data is preprocessed so that the noise and the fault signature of the bearings are separated. Then, CNN models are developed and trained to learn significant features containing information of defects. Lastly, the CNN models are examined and validated whether they learn and extract the meaningful features or not.

scholarly journals Overview and perspective of nonwoven agrotextile

2019 ◽  
Vol 2 (1) ◽  
pp. 32-45 ◽  
Author(s):  
Paula Marasović ◽  
Dragana Kopitar
Keyword(s):  
Thermal Protection ◽  
Environmental Concern ◽  
Cost Effective ◽  
Weather Conditions ◽  
Natural Fibre ◽  
Potential Candidate ◽  
Food Quantity ◽  
Technical Textiles ◽  
The World ◽  
Agricultural Applications

Agrotextile belongs to one of the twelve sectors of technical textiles covering textile products with application in agriculture, horticulture, cattle breeding and aquaculture as well in agro engineering. The significance of agrotextiles can be stated substantial all over the world since it has been proven to be very versatile and cost effective materials. Nonwoven agrotextiles are innovative products with special structural performances designed for agricultural applications and practices such as weed control, wind protection, frost cover fabric that is used for adjustment of weather conditions from the sudden changing of temperature and seasonal changes. Furthermore, common application of nonwoven agrotextiles are for reducing the sun radiation as well as thermal protection of plants as shade cloth, furthermore for preventing insect and other pests on crops, preventing soil drainage and sediment creation. All over the world, applications of nonwoven agrotextiles products in agriculture have shown great positive impacts on growth, production and protection of various crops and vegetables. Many studies have been proving that nonwoven agrotextile covers accelerate the growth and development of seedlings as well as their nutritive values. By preventing weed growth and insect protection, the use of herbicides and pesticides are reduced. Agrotextiles made of natural fibres can be considered as a potential candidate for replacing some of today’s popular synthetic agrotextiles which are becoming ecologically less acceptable nowadays. Usage of agrotextiles is one of the growing alternatives in today’s context with respect to the increase in global population thus food quantity and food quality and in the same time growing environmental concern. Sustainable socio-economic development considers natural fibre usage in agrotextile production in all possible areas covered by agrotextile application. The main purpose of the review is to give an overview and importance of nonwoven agrotextiles with indication of nonwoven agrotextile perspective in future.

Research on a beef tenderness detection method using a bionic mastication system based on a pressure sensor

2017 ◽  
Vol 9 (32) ◽  
pp. 4695-4701 ◽  
Author(s):  
Xiaodan Wang ◽  
Hongmei Wang ◽  
Yingming Cai ◽  
Jiahui Jin ◽  
Lingtao Zhu ◽  
...  
Keyword(s):  
Pressure Sensor ◽  
Detection Method ◽  
High Accuracy ◽  
Meat Tenderness ◽  
Beef Tenderness ◽  
Novel Method

A novel method using bionic mastication system based on a pressure sensor was developed to predict beef tenderness with convenience, stability and high accuracy. What's more, this method can be applied to detect other meat tenderness such as those of chicken and pork as well, which indicates a universality of this method.

Measurement of Vehicle Tire Footprint Pattern and Pressure Distribution Using Piezoresistive Force Sensor Mat and Image Analysis

2010 ◽  
Vol 437 ◽  
pp. 467-471 ◽  
Author(s):  
Rong Sheng Lu ◽  
Ning Liu ◽  
Xiao Huai Chen
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Pressure Distribution ◽  
Digital Image Processing ◽  
Force Sensor ◽  
High Accuracy ◽  
Envelope Curve ◽  
Calculation Algorithm ◽  
Measurement Principle ◽  
Novel Method

In this paper, a novel method to measure the footprint pattern of a vehicle tire and its pressure distribution will be put forward. The measurement principle will be presented. The automatic digital image processing methods of the footprint pattern and pressure distribution images, which are used to characterize the footprint pattern, are described. Especially, a novel envelope curve calculation algorithm for finding a pattern boundary is introduced. The experimental results have shown that the methods mentioned in the paper are of robustness and high accuracy.

Sign in / Sign up

Export Citation Format

Share Document