Machine Vision and Machine Learning based Fruit Quality Monitoring

The efficiency of the logistics of agricultural food needs to assure that its products are safe and of quality. This would earn the trust of consumers. To provide smart farming and packing solutions, the proposed work is an intelligent system using machine learning and image processing on Apple quality detection. The Apple image dataset was used with two stages of fruit, one is healthy and another one is damaged. The machine learning model is trained with this dataset to identify the fruit quality. The proposed technique uses feature extraction using image processing technique and SVM algorithm is applied to train and detect the quality of fruit.

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Design and Development of an Intelligent System for Pothole and Hump Identification on Roads

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c5936.098319 ◽

2019 ◽

Vol 8 (3) ◽

pp. 5294-5300 ◽

Cited By ~ 1

Keyword(s):

Image Processing ◽

Fuel Consumption ◽

Intelligent System ◽

Processing Technique ◽

Simple Solution ◽

Image Processing Technique ◽

Raspberry Pi ◽

Ultrasonic Sensors ◽

Design And Development ◽

Geographical Position

Country’s economy depend on well-maintained roads as they are major means of transportation. It becomes essential to identify pothole and humps in order to avoid accidents and damages to the vehicles that is caused because of distress to drivers and also to save fuel consumption. In this regard, this work presents a simple solution to detect potholes and humps and hence avoid accidents and help drivers. Potholes are detected using Image Processing Technique and Ultrasonic Sensors are used to detect humps. Controlling device used is Raspberry Pi. The system acquires the geographical position of potholes using Wi-Fi and transmits it to authorities to take corrective measures

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Fruit Quality Analysis using Image Processing

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.e9309.069520 ◽

2020 ◽

Vol 9 (5) ◽

pp. 88-91

Keyword(s):

Image Processing ◽

Feature Extraction ◽

Fruit Quality ◽

Processing Technique ◽

Image Processing Technique ◽

Quality Analysis ◽

Quality Inspection ◽

Critical Comparison ◽

Texture Size ◽

Vegetable Quality

Fruit Analysis using image processing is a technique used for finding the detection of fruits by a specific algorithm. This project is also used in finding the defected fruit in a group of fruits by the image processing technique. The objective of this work is to prevent health hazards by eating that defected fruit. This processing technique undergoes several stages for the classification and prediction of the defective fruit. This paper presents a detailed overview of various methods i.e., preprocessing, segmentation, feature extraction, a designation that addressed fruits and vegetable quality based on color, texture, size, shape, and defects. In this paper, a critical comparison of a different algorithm proposed by researchers for quality inspection of fruits has been carried out.

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A New Image Processing Technique for STEM

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100052171 ◽

1974 ◽

Vol 32 ◽

pp. 432-433

Author(s):

Yasushi Kokubo ◽

Hirotami Koike ◽

Teruo Someya

Keyword(s):

Electron Microscopy ◽

Image Processing ◽

Scanning Electron Microscopy ◽

Elastic Scattering ◽

Field Emission ◽

Processing Technique ◽

Image Processing Technique ◽

Energy Analyzer ◽

Scanning Microscope ◽

Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

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A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit183863 ◽

2018 ◽

pp. 194-200

Author(s):

J. Magelin Mary ◽

Chitra K. ◽

Y. Arockia Suganthi

Keyword(s):

Genetic Algorithm ◽

Image Processing ◽

Medical Image ◽

Medical Image Processing ◽

Processing Technique ◽

Input Image ◽

Image Processing Technique ◽

Computational Time ◽

Image Mining ◽

The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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An Enhanced Technique for Classification of Fruits using Shape Color and Texture Features

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse/v7i7/0107 ◽

2017 ◽

Vol 7 (7) ◽

pp. 408

Author(s):

Yashpal Jitarwal ◽

Tabrej Ahamad Khan ◽

Pawan Mangal

Keyword(s):

Image Processing ◽

Texture Features ◽

Automatic Classification ◽

Processing Technique ◽

Image Processing Technique ◽

Advance Technique ◽

Time Required ◽

Fruit Sorting ◽

Human Inspection

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.

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