scholarly journals Application of Digital Image Analysis to the Prediction of Chlorophyll Content in Astragalus Seeds

2021 ◽  
Vol 11 (18) ◽  
pp. 8744
Author(s):  
Yanan Xu ◽  
Keling Tu ◽  
Ying Cheng ◽  
Haonan Hou ◽  
Hailu Cao ◽  
...  
Keyword(s):  
Image Analysis ◽  
Chlorophyll Content ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Low Cost ◽  
High Price ◽  
Multiple Features ◽  
Characteristic Features ◽  
Mlp Model

Chlorophyll fluorescence (CF) has been applied to measure the chlorophyll content of seeds, in order to determine seed maturity, but the high price of equipment limits its wider application. Astragalus seeds were used to explore the applicability of digital image analysis technology to the prediction of seed chlorophyll content and to supply a low cost and alternative method. Our research comprised scanning and extracting the characteristic features of Astragalus seeds, determining the chlorophyll content, and establishing a predictive model of chlorophyll content in Astragalus seeds based on characteristic features. The results showed that the R2 of the MLR prediction model established with multiple features was ≥0.947, and the R2 of the MLP model was ≥0.943. By sorting of two single features, the R and G values, the R2 reached 0.969 and 0.965, respectively. A germination result showed that the lower the chlorophyll content, the higher the quality of the seeds. Therefore, we draw a conclusion that digital image analysis technology can be used to predict effectively the chlorophyll content of Astragalus seeds, and provide a reference for the selection of mature and viable Astragalus seeds.

scholarly journals Digital Image Analysis of the Angle and Optic Nerve: A Simple, Fast, and Low-Cost Method for Glaucoma Assessment

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Greg Russell ◽  
Silvia N. W. Hertzberg ◽  
Natalia Anisimova ◽  
Natalia Gavrilova ◽  
Beáta É. Petrovski ◽  
...  
Keyword(s):  
Image Analysis ◽  
Optic Nerve ◽  
Nerve Fiber ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Low Cost ◽  
Detection Methods ◽  
Slit Lamp ◽  
Image Subtraction ◽  
Oct Imaging

Purpose. To devise a simple, fast, and low-cost method for glaucoma assessment using digital image analysis of the angle and optic nerve in human subjects. Methods. Images from glaucoma and fundus assessment were used in this study, including color fundus photographs, standard optic nerve optical coherence tomography (OCT), and digital slit-lamp images of the angle/gonioscopy. Digital image conversion and analysis of the angle using ImageJ (NIH, USA) and adaptive histogram equalization contrast-limited AHE (CLAHE) to prevent noise amplification were implemented. Angle and optic nerve images were analyzed separately in the red, green, and blue (RGB) channels followed by 3D volumetric analysis of the degrees of angle depth and cup volume of the optic nerve. Horizontal tomogram reconstitution and nerve fiber detection methods were developed and compared to standard OCT images. Results. Digital slit-lamp angle images showed similar accuracy as standard anterior OCT measurements. Comparative analysis of RGB channels produced volumetric cup and horizontal tomogram, which closely resembled the 3D OCT appearance and B-scan of the cup, respectively. RGB channel splitting and image subtraction produced a map closely resembling that of the retinal nerve fiber layer (RNFL) thickness map on OCT. Conclusions. While OCT imaging is rapidly progressing in the area of optic disc and chamber angle assessment, rising healthcare costs and lack of availability of the technology open a demand for alternative and cost-minimizing forms of image analysis in glaucoma. Volumetric, geometric, and segmentational data obtained through digital image analysis correspond well to those obtained by OCT imaging.

scholarly journals DIGITAL IMAGE ANALYSIS BASED ON AUTOMATED COUNTING CLUSTERED SOYBEAN SEEDS

2014 ◽  
Vol 12 (3) ◽  
pp. 3325-3328
Author(s):  
Jasdeep Kaur
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Low Cost ◽  
Detection Algorithm ◽  
Soya Bean ◽  
Soybean Seeds ◽  
Manual Counting ◽  
Processing Steps ◽  
Image Analysis Techniques

-  This paper investigates the use of digital image analysis techniques for developing for counting clustered soya bean seeds. Images are extracted from source WWW.21food.com). As manual counting have several issues such as low accuracy and higher cost. Automated counting techniques give a fast and low cost of counting soya bean seeds. This paper follows 5 processing steps. First process converting the image into gray scale and thresholding is applied using CLAHE. Second dilation is applied to enhance the image. Third applied masking to enhance the image. Fourth edge detection algorithm is applied. Fifth step beans extracted with respect to bean shape. 

A portable, low-cost, smartphone assisted methodology for on-site measurement of NO2 levels in ambient air by selective chemical reactivity and digital image analysis

2021 ◽  
Vol 338 ◽  
pp. 129867
Author(s):  
Maria Cerrato-Alvarez ◽  
Samuel Frutos-Puerto ◽  
Patricia Arroyo ◽  
Conrado Miró-Rodríguez ◽  
Eduardo Pinilla-Gil
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Chemical Reactivity ◽  
Low Cost ◽  
Ambient Air ◽  
Selective Chemical

scholarly journals Tools for Evaluating Native Grasses as Low Maintenance Turf

2009 ◽  
Vol 19 (3) ◽  
pp. 626-632 ◽  
Author(s):  
Landon D. Bunderson ◽  
Paul G. Johnson ◽  
Kelly L. Kopp ◽  
Adam Van Dyke
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Objective Evaluation ◽  
West Region ◽  
Quality Ratings ◽  
Evapotranspiration Rate ◽  
Color Data ◽  
Turfgrass Quality

Visual ratings are the standard for evaluating turfgrass quality. However, to provide more objective evaluations and to address statistical concerns, other methods have been developed to measure turfgrass quality, including digital image analysis and measurements of chlorophyll content. These have been largely applied to traditionally used turfgrass species, but here we used these methods to evaluate turfgrass quality of nontraditional species and mixtures that are native or adapted to the intermountain west region of North America. Two fertilizer treatments (1.0 or 2.0 lb/1000 ft2 nitrogen) were applied to 21 different species and species mixtures in North Logan, UT. These plots were irrigated to replace 60% of the local evapotranspiration rate and were mowed at 4 inches. Turfgrass quality ratings were most effective in measuring quality among the diverse species used in this study. Because of the wider variation in acceptable visual characteristics and lower quality expectations for low-maintenance native turf, the objective evaluation methods proved less useful. Generally, chlorophyll meter data, digital image analysis of cover, and digital image analysis of color data were not well correlated with human visual quality ratings in this study. Measurements were well correlated in some species, but not in others. These methods can supplement, but cannot replace, human visual turfgrass quality ratings for comparison of dissimilar grasses.

scholarly journals Estimation of PM10 Levels and Sources in Air Quality Networks by Digital Analysis of Smartphone Camera Images Taken from Samples Deposited on Filters

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4791 ◽  
Author(s):  
Selena Carretero-Peña ◽  
Lorenzo Calvo Blázquez ◽  
Eduardo Pinilla-Gil
Keyword(s):  
Image Analysis ◽  
Air Quality ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Low Cost ◽  
Gravimetric Method ◽  
Ambient Air ◽  
Saharan Dust ◽  
Aerosol Sampling ◽  
Digital Analysis

This paper explores the performance of smartphone cameras as low-cost and easily accessible tools to provide information about the levels and origin of particulate matter (PM) in ambient air. We tested the concept by digital analysis of the images of daily PM10 (particles with diameters 10 µm and smaller) samples captured on glass fibre filters by high-volume aerosol samplers at urban and rural locations belonging to the air quality monitoring network of Extremadura (Spain) for one year. The images were taken by placing the filters inside a box designed to maintain controlled and reproducible light conditions. Digital image analysis was carried out by a mobile colour-sensing application using red, green, blue/hue, saturation, value/hue, saturation, luminance (RGB/HSV/HSL) parameters, that were processed through statistical procedures, directly or transformed to greyscale. The results of the study show that digital image analysis of the filters can roughly estimate the concentration of PM10 within an air quality network, based on a significant linear correlation between the concentration of PM10 measured by an official gravimetric method and the colour parameters of the filters’ images, with better results in the case of the saturation parameter (SHSV). The methodology based on digital analysis can discriminate urban and rural sampling locations affected by different local particle-emitting sources and is also able to identify the presence of remote sources such as Saharan dust outbreaks in both urban and rural locations. The proposed methodology can be considered as a useful complement to the aerosol sampling equipment of air quality network field units for a quick estimation of PM10 in the ambient air, through a simple, accessible and low-cost procedure, with further miniaturization potential.

Digital Image Analysis Improves the Quality of Subjective HER-2 Expression Scoring in Breast Cancer

2008 ◽  
Vol 16 (2) ◽  
pp. 185-190 ◽  
Author(s):  
Ivar Skaland ◽  
Irene Øvestad ◽  
Emiel A. M. Janssen ◽  
Jan Klos ◽  
Kjell H. Kjellevold ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Her 2

Digital Image Analysis of the Larynx

2000 ◽  
Vol 10 (2) ◽  
pp. 7-9
Author(s):  
Yaser Natour ◽  
Christine Sapienza ◽  
Mark Schmalz ◽  
Savita Collins
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis
Sign in / Sign up

Export Citation Format

Share Document