scholarly journals Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 112 ◽  
Author(s):  
Andrzej Przybylak ◽  
Radosław Kozłowski ◽  
Ewa Osuch ◽  
Andrzej Osuch ◽  
Piotr Rybacki ◽  
...  
Keyword(s):  
Image Analysis ◽  
Neural Model ◽  
Assessment Method ◽  
Analysis Method ◽  
Potato Tubers ◽  
Specialized Knowledge ◽  
Analysis Techniques ◽  
Quality Assessment Method ◽  
Sorting Process ◽  
Image Analysis Techniques

This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

scholarly journals The Use of the Image Analysis Method for the Segregation of Shredded Waste in An Air Classifier

2014 ◽  
Vol 13 (2) ◽  
pp. 97-107
Author(s):  
Irmina Zagaj ◽  
Roman Ulbrich
Keyword(s):  
Image Analysis ◽  
Waste Management ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Analysis Techniques ◽  
Pneumatic Classification ◽  
Air Classifier ◽  
Image Analysis Techniques

Abstract Segregation of shredded waste is one of the technologies of waste management, along with issues related to manual segregation, while nowadays it starts to be associated with pneumatic classification. This paper discusses the use of an air classifier and image analysis techniques for the purposes of evaluation of segregation of shredded waste. This type of air classifier plays an important role due to the efficiency of the device and the characteristics of segregation. The authors report the results of research into image analysis of segregation of shredded waste on the basis of the use of image analysis.

scholarly journals Fibre length by electronic image analysis

1992 ◽  
Vol 11 ◽  
pp. 1-30
Author(s):  
Torsten Hoelstad
Keyword(s):  
Image Analysis ◽  
Fibre Length ◽  
Image Analysis System ◽  
Analysis Method ◽  
Analysis Techniques ◽  
Glass Fibres ◽  
Analysis System ◽  
Image Analysis Techniques ◽  
Glycerol Jelly ◽  
Fibre Preparation

A number of electronic image analysis techniques have been applied to preparations of glass fibres obtained from polymer based composites (PES and PPS matrix) in order to automate length measurements. The image analysis sequence developed is described in detail. The functions of the sequence are based mainly on aspects of filtering in the spatial domain by means of convolution, mathematical morphology and conditional measuring. The key image analysis function is directional erosion. Using glycerol jelly strew preparations and transmitted light, the length of 500 glass fibres can be automatically measured in approximately 15 minutes with an array processor-based image analysis system (IBAS 2). The image analysis method is tolerant of impurities and variations in fibre preparation density; the method produces consistent results and errors due to misinterpretation are negligible.

A Review on Automatic Bill of Material Generation and Visual Inspection on PCBs

2019 ◽  
Author(s):  
Mukhil Azhagan M. S ◽  
Dhwani Mehta ◽  
Hangwei Lu ◽  
Sudarshan Agrawal ◽  
Mark Tehranipoor ◽  
...  
Keyword(s):  
Image Analysis ◽  
Visual Inspection ◽  
Automated System ◽  
Imaging Modalities ◽  
Future Research ◽  
Analysis Techniques ◽  
Bill Of Materials ◽  
Pros And Cons ◽  
Index Terms ◽  
Image Analysis Techniques

Abstract Globalization and complexity of the PCB supply chain has made hardware assurance a challenging task. An automated system to extract the Bill of Materials (BoM) can save time and resources during the authentication process, however, there are numerous imaging modalities and image analysis techniques that can be used to create such a system. In this paper we review different imaging modalities and their pros and cons for automatic PCB inspection. In addition, image analysis techniques commonly used for such images are reviewed in a systematic way to provide a direction for future research in this area. Index Terms—Component Detection, PCB, Authentication, Image Analysis, Machine Learning

scholarly journals Using PhotoCube as an extensible demonstration platform for advanced image analysis techniques

2012 ◽  
Author(s):  
Grimur Tomasson ◽  
Gisli Kristjan Olafsson ◽  
Hlynur Sigurporsson ◽  
Bjorn Por Jonsson ◽  
Kristjan Runarsson ◽  
...  
Keyword(s):  
Image Analysis ◽  
Analysis Techniques ◽  
Image Analysis Techniques

Considerations for Whole-Slide Analysis of Murine Xenografts Experiments

2021 ◽  
Vol 69 (10) ◽  
pp. 627-631
Author(s):  
Abigail R. Bland ◽  
John C. Ashton
Keyword(s):  
Cell Death ◽  
Image Analysis ◽  
Cell Counting ◽  
Analysis Techniques ◽  
The Core ◽  
Necrotic Region ◽  
Areas Of Interest ◽  
Image Analysis Techniques ◽  
Immunohistochemical Analyses ◽  
Animal Models Of Cancer

Histochemistry of tumor sections is a widely employed technique utilized to examine cell death in preclinical xenograft animal models of cancer. However, this is under the assumption that tumors are homogeneous, leading to practices such as automatic cell counting across the entire section. We have noted that in our experiments the core of the tumor is largely or partially necrotic, and lacks evidence of vascularization (in contrast to the outer areas of the tumor). We note that this can bias and confound immunohistochemical analyses that do not take care to sample areas of interest in a way to take this into account. Design-based stereology with image analysis techniques is an alternative process that could be used to measure the volume of the necrotic region compared to the volume of the whole tumor.

scholarly journals AN AUTOMATED FRAMEWORK FOR CORONARY ANALYSIS FROM CORONARY CINE ANGIOGRAMS USING MACHINE LEARNING AND IMAGE ANALYSIS TECHNIQUES

2021 ◽  
Vol 9 (1) ◽  
pp. 1406-1412
Author(s):  
K. Santhi, A. Rama Mohan Reddy
Keyword(s):  
Machine Learning ◽  
Cardiovascular Disease ◽  
Image Analysis ◽  
Visual Assessment ◽  
Disease Diagnosis ◽  
Healthy Life ◽  
Common Cause ◽  
Analysis Techniques ◽  
Image Modality ◽  
Image Analysis Techniques

Cardiovascular disease (CVD) is one of the critical diseases and the most common cause of morbidity and mortality worldwide. Therefore, early detection and prediction of such a disease is extremely essential for a healthy life. Cardiac imaging plays an important role in the diagnosis of cardiovascular disease but its role has been limited to visual assessment of heart structure and its function. However, with the advanced techniques and tools of big data and machine learning, it become easier to clinician to diagnose the CVD. Stenosis with in the Coronary Arteries (CA) are often determined by using the Coronary Cine Angiogram (CCA). It comes under the invasive image modality. CCA is the effective method to detect and predict the stenosis. In this paper a coronary analysis automation method is proposed in disease diagnosis. The proposed method includes pre-processing, segmentation, identifying vessel path and statistical analysis.

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