Method for Grade Identification of Tobacco Based on Machine Vision

2018 ◽  
Vol 61 (5) ◽  
pp. 1487-1495
Author(s):  
Yan He ◽  
Haijun Wang ◽  
Shiping Zhu ◽  
Tao Zeng ◽  
Zhenzhen Zhuang ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Machine Vision ◽  
Recognition Algorithm ◽  
Identification System ◽  
Tobacco Leaves ◽  
Tobacco Leaf ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern ◽  
Model Set

Abstract. Tobacco grading is the first step in the transfer of tobacco leaves from agricultural products to commodities and is key to determining the quality of tobacco. Manual grading is conventionally used for tobacco grading. However, it is time-consuming, expensive, and may require specialized labor. To overcome these limitations, a method for grade identification of tobacco leaves based on machine vision is proposed in this article. Based on a fuzzy pattern recognition algorithm, the tobacco leaf samples of the model set and prediction set could be classified by extracting appearance characteristics of the tobacco leaves. The identification system for tobacco leaves based on fuzzy pattern recognition was developed in MATLAB. The rate of correct grading was 85.81% and 80.23% for the modeling set and prediction set, respectively. This result shows that machine vision based automatic tobacco grading has a great advantage over manual grading, and this method can be explored for viable commercial use. Keywords: Fuzzy pattern recognition, Grade identification, Machine vision, Tobacco leaf.

The Research of Label Identification Method Based on Fuzzy Theory

2013 ◽  
Vol 756-759 ◽  
pp. 4100-4102
Author(s):  
Xiao Yu Bu ◽  
Ping Liu
Keyword(s):  
Pattern Recognition ◽  
Fuzzy Theory ◽  
Automatic Identification ◽  
Identification System ◽  
Control Effect ◽  
Key Technology ◽  
Automatic Identification System ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern

This paper is mainly discussing the key technology of label automatic identification system using the indirect fuzzy pattern recognition based on the features of image and the fuzzy theory. This method greatly improves the efficiency and accuracy and the control effect is obvious, so that the quality of the label is guaranteed.

Research of Ultrasonic Detection for Bonding Quality of Thin Plate Based on Fuzzy Pattern Recognition

2011 ◽  
Vol 346 ◽  
pp. 493-500
Author(s):  
Xiao Juan Wang ◽  
Ze Zhang ◽  
Hai Tao Wang
Keyword(s):  
Pattern Recognition ◽  
Recognition Algorithm ◽  
Fuzzy Membership Function ◽  
Practical Application ◽  
Ultrasonic Detection ◽  
Bonding Quality ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern ◽  
Fuzzy Subsets

The application of fuzzy pattern recognition to ultrasonic detection for bonding quality of thin composite plate is studied. In this paper, firstly, the fuzzy membership function between each characteristic and bonding quality is established by BP neural network. Simulation results show that this method is convenient, simple, and it conforms to the practical application. Accordingly，the fuzzy subsets of standard modules and unknown bonding quality modules are established. Secondly, the fuzzy pattern recognition algorithm, which is designed by the nearest principle as the judging standard to judge bonding quality, is given. Experimental results show that the algorithm is very exact for quantitative recognition of bonding quality.

Vehicle Model Recognition Based on Fuzzy Pattern Recognition Method

2011 ◽  
Vol 383-390 ◽  
pp. 4799-4802
Author(s):  
Yi Qiang Wang ◽  
Rui Jian Huang ◽  
Tian Yi Xu ◽  
Ke Hong Tang
Keyword(s):  
Pattern Recognition ◽  
Recognition Algorithm ◽  
Good Effect ◽  
Feature Points ◽  
Recognition Method ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern ◽  
Characteristic Values ◽  
Membership Matrix ◽  
Model Recognition

The method based on the theory of Fuzzy Pattern Recognition is divided into three parts. Firstly, use Hough transformation to extract the feature points of vehicles, and use the ratio between two absolute distance of adjacent feature points as the characteristic values of vehicles; secondly, use Fuzzy C-mean Classification to handle feature data of 75 car model, then establish a degree of membership matrix as the sample space; thirdly, consider the classification algorithm based on fuzzy approach degree and the credibility of the vehicle feature to propose a weighted close- degree recognition algorithm. This recognition method has a good effect.

scholarly journals Cold stress in the harvest period: effects on tobacco leaf quality and curing characteristics

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yan Li ◽  
Ke Ren ◽  
Mengyang Hu ◽  
Xian He ◽  
Kaiyuan Gu ◽  
...  
Keyword(s):  
Cold Stress ◽  
High Altitude ◽  
Weather Forecast ◽  
Production Quality ◽  
Chemical Components ◽  
Leaf Quality ◽  
Tobacco Leaves ◽  
Tobacco Leaf ◽  
Antioxidant Enzyme System

Abstract Background Weather change in high-altitude areas subjects mature tobacco (Nicotiana tabacum L.) to cold stress, which damages tobacco leaf yield and quality. A brupt diurnal temperature differences (the daily temperature dropping more than 20 °C) along with rainfall in tobacco-growing areas at an altitude above 2450 m, caused cold stress to field-grown tobacco. Results After the flue-cured tobacco suffered cold stress in the field, the surface color of tobacco leaves changed and obvious large browning areas were appeared, and the curing availability was extremely poor. Further research found the quality of fresh tobacco leaves, the content of key chemical components, and the production quality were greatly reduced by cold stress. We hypothesize that cold stress in high altitude environments destroyed the antioxidant enzyme system of mature flue-cured tobacco. Therefore, the quality of fresh tobacco leaves, the content of key chemical components, and the production quality were greatly reduced by cold stress. Conclusion This study confirmed that cold stress in high-altitude tobacco areas was the main reason for the browning of tobacco leaves during the tobacco curing process. This adverse environment seriously damaged the quality of tobacco leaves, but can be mitigated by pay attention to the weather forecast and pick tobacco leaves in advance.

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