Nondestructive Evaluation System for White Ginseng Quality Using Image Processing Technique

A real-time white ginseng quality evaluation system based on a machine vision technique and artificial neural networks was developed to replace the current manual grading and its efficiency was tested. The system consisted of conveyor, image acquisition system synchronized with a sample-detecting sensor, and image processing and decision-making system. Software running under Windows system was developed. The algorithm included three consecutive stages of (a) image acquisition and preprocessing, (b) mathematical feature extraction, and (c) grade decision using artificial neural networks. Mathematical features such as area ratio, mean and standard deviation of gray level, skewness of gray level histogram, and the number of run segment, were extracted from five equally divided parts of a specimen. An artificial neural network model was used to classify samples into three grading categories. The grading error of the system was about 26%, which is comparable to the 30% in case of manual grading. The grading rate was one sample per a second.

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The evaluation system of fabric pilling based on image processing technique

2009 International Conference on Image Analysis and Signal Processing ◽

10.1109/iasp.2009.5054639 ◽

2009 ◽

Cited By ~ 2

Author(s):

Liu Xiaojun ◽

Han Huabing ◽

Lu Yushu ◽

Zhao Hong

Keyword(s):

Image Processing ◽

Evaluation System ◽

Processing Technique ◽

Image Processing Technique ◽

The Evaluation System

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Application of Image Processing Technique for Evaluation of Garment Pleats

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.332-334.854 ◽

2011 ◽

Vol 332-334 ◽

pp. 854-859

Author(s):

Wei Wei Chen ◽

Yan Chen

Keyword(s):

Image Processing ◽

Evaluation System ◽

Processing Technique ◽

Image Processing Technique ◽

Visual Effects ◽

Research Results ◽

Grey Scale ◽

Digital Expression ◽

Image Technique

The trends and results achieved on application of image processing technique in the textile and garment were reviewed. The basis and principle of application of image technique to the garment pleat evaluation were studied. A blouse wearer trial is conducted so that the images of wrinkles developed on the surface of the blouse with different postures of the wearer were collected. The visual effects of the garment pleats created by various techniques and wearing were analyzed, and methods for extracting pleat images form the surface of the fabric were also introduced. After image processing of the extracted pleats, an evaluation system of garment pleats based on the grey scale was recommended, which included such indexes as the number, depth and width of pleat, and unevenness of pleats. The study took an example of the wrinkles changing in a blouse sleeve when arm lifting, which proved the feasibility of digital expression of wrinkle characteristics by mean s of image technique theoretically and practically. Research results indicated that this evaluation system can truly reflect the form and characteristics of garment pleats．

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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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