An automatic sorting system for fresh white button mushrooms based on image processing

2018 ◽  
Vol 151 ◽  
pp. 416-425 ◽  
Author(s):  
Fengyun Wang ◽  
Jiye Zheng ◽  
Xincheng Tian ◽  
Jianfei Wang ◽  
Luyan Niu ◽  
...  
Keyword(s):  
Image Processing ◽  
Automatic Sorting ◽  
Button Mushrooms ◽  
Sorting System ◽  
White Button Mushrooms

Measuring the Cap Diameter of White Button Mushrooms ( Agaricus bisporus ) by Using Depth Image Processing

2021 ◽  
Vol 37 (4) ◽  
pp. 623-633
Author(s):  
Jiangtao Ji ◽  
Jingwei Sun ◽  
Xin Jin ◽  
Hao Ma ◽  
Xuefeng Zhu
Keyword(s):  
Image Processing ◽  
Measurement Error ◽  
Agaricus Bisporus ◽  
Detection Rate ◽  
Depth Image ◽  
Diameter Measurement ◽  
Selective Harvesting ◽  
Background Segmentation ◽  
Button Mushrooms ◽  
White Button Mushrooms

Highlights A new background segmentation algorithm for depth image was developed. Cap diameter of white button mushroom was measured automatically. The average of diameter measurement error was 4.94%. This work can provide online decision support for selectively harvesting of Agaricus bisporus . Abstract. With the increase in the production and yield of white button mushrooms (Agaricus bisporus), efficient harvesting has become a challenge. Automatic selective harvesting has gradually become a solution. The diameter of the mushroom cap is an essential indicator of the harvesting standard. To provide guidance for selective harvesting, this article presents a method for target detection and measuring the diameter of mushroom caps by using depth image processing. According to the three-dimensional structure characteristics of the mushroom, a novel method is proposed to segment it from the compost it grows on. In this method, compost is regarded as the floor of the sea and mushrooms as standing islands. With the rise of sea level, the compost is gradually submerged, and the target of Agaricus bisporus is stable. These features were used to realize the background segmentation. After background segmentation, the pixel coordinates of the contour points of the mushroom caps are transformed into world coordinates, and the cap diameter is measured by Hough transform. In total, 380 mushrooms depicted in 25 depth images were used to test the developed algorithms. The results showed that 92.37% of the mushrooms were correctly detected. The missed detection rate was less than 8%, and the false detection rate was 1.96%. The average diameter measurement error was 4.94%, and the average process time to measure a single mushroom was approximately 0.50 s. The method proposed in this article can provide online decision support for automatic selective harvesting of Agaricus bisporus, which can improve the quality and efficiency of its production. Keywords: Background segmentation, Computer vision, Diameter measurement, Edible fungus, Hough transform.

A Pearl Automatic Sorting System Based on Image Identification

2014 ◽  
Vol 496-500 ◽  
pp. 1574-1577
Author(s):  
Zhen Lin Bai ◽  
Qin Run Wen ◽  
Mei Yang
Keyword(s):  
Image Processing ◽  
Numerical Control ◽  
Control Technology ◽  
Image Identification ◽  
Automatic Sorting ◽  
Market Competitiveness ◽  
Manual Sorting ◽  
Computer Image Processing ◽  
Sorting System ◽  
Positive Effect

This paper introduces a pearl automatic sorting system. The design conforms to the national condition of our country. With the use of pearl automatic sorting system, automatic sorting instead of the cumbersome manual sorting workers. It uses computer image processing technology and numerical control technology. It has a positive effect to guarantee product quality. And it can improve the market competitiveness of enterprises.

scholarly journals Digital Image Processing Technology in Design and Development of Automatic Sorting System for Energy Meter Recovery

2021 ◽  
Vol 2143 (1) ◽  
pp. 012042
Author(s):  
Hao Hu ◽  
Bo Liu ◽  
Wen Jie Li ◽  
He Liu Sun ◽  
Tang Sen Ni
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Artificial Neural Network ◽  
Digital Image Processing ◽  
Digital Image ◽  
Processing Technology ◽  
Automatic Sorting ◽  
Image Processing Technology ◽  
Artificial Neural ◽  
Sorting System

Abstract In order to solve the problems of low sorting efficiency and poor quality caused by manual sorting in traditional electricity meter recovery, this study adopts digital image processing technology to construct an automatic sorting system for electricity meter recovery based on artificial neural network. Firstly, the basic requirements of system construction are analyzed in detail, and then the principle and method of image recognition of artificial neural network are introduced in detail. On this basis, an overall framework of automatic sorting of electricity meter recovery is constructed. Finally, the functional modules are designed and applied, and Azure database is built through SQL Server platform, so as to realize the system application of this research. The final application shows that the automatic sorting system constructed by this study has simple interface and easy operation, which can greatly improve the efficiency and quality of the electricity meter recycling and sorting, and has certain practical significance for the development of the state grid industry.

scholarly journals Enhancement in physicochemical parameters and microbial populations of mushrooms as influenced by nano-coating treatments

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rokayya Sami ◽  
Abeer Elhakem ◽  
Amina Almushhin ◽  
Mona Alharbi ◽  
Manal Almatrafi ◽  
...  
Keyword(s):  
Physicochemical Parameters ◽  
Microbial Growth ◽  
Research Work ◽  
Microbial Populations ◽  
Coating Film ◽  
Epidermal Structure ◽  
Nano Coating ◽  
Soluble Solid ◽  
Button Mushrooms ◽  
White Button Mushrooms

AbstractWhite button mushrooms are greatly high perishable and can deteriorate within a few days after harvesting due to physicomechanical damage, respiration, microbial growth of the delicate epidermal structure. For that reason, the present research work was applied to evaluate the effect of chitosan combination with nano-coating treatments on physicochemical parameters and microbial populations on button mushrooms at chilling storage. Nano coating with the addition of nisin 1% (CHSSN/M) established the minimum value for weight loss 12.18%, maintained firmness 11.55 N, and color index profile. Moreover, O2% rate of (CHSSN/M) mushrooms was the lowest at 1.78%; while the highest rate was reported for CO2 24.88% compared to the untreated samples (Control/M) on day 12. Both pH and total soluble solid concentrations increased during storage. Results reported that the (CHSS/M) mushroom significantly (P < 0.05) reduced polyphenol oxidase activity (24.31 U mg−1 Protein) compared with (Control/M) mushrooms that increased faster than the treated samples. (CHSSN/M) treatment was the most efficient in the reduction of yeast and mold, aerobic plate microorganisms (5.27–5.10 log CFU/g), respectively. The results established that nano-coating film might delay the aging degree and accompany by marked prolongation of postharvest mushroom freshness.

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