The Digital Method of Clothing Extension Measurement

2011 ◽  
Vol 175-176 ◽  
pp. 807-810
Author(s):  
Zhi Ge Chen ◽  
Qing Guan Chen
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Noise ◽  
Digital Method ◽  
Stripe Width ◽  
Fabric Strength ◽  
The Relationship

Fabric extension can be measured by using fabric strength tester in laboratory. But the extension is difficult to be measured when the clothing is in wearing. In this paper, the relationship between the extension of clothing and the fabric tension was discussed according to the experiment result. The digital image processing will be used to grab clothing images and to measure the extension of fabric. The techniques of digital image processing, such as binary conversion of image, noise points deleting, smooth processing of stripe edge and the stripe width measuring, were applied in this research. Based on experiment results, the relation between the fabric tension and extension were linear when the clothing was under the condition of small strength.

Comparative Analysis on Noise Processing of Image

2013 ◽  
Vol 718-720 ◽  
pp. 2159-2162
Author(s):  
Hua Jun Dong ◽  
Xue Mei Jiang ◽  
Chen Xu Niu
Keyword(s):  
Image Processing ◽  
Comparative Analysis ◽  
Digital Image Processing ◽  
Digital Image ◽  
Median Filter ◽  
Wiener Filter ◽  
Image Noise ◽  
Two Dimensional ◽  
Wavelet Filter ◽  
Average Filter

The existence of noises have great interference on image processing, so the elimination of image noise is of great importance. In this paper, based on the digital image processing, the methods of average filter, wiener filter, median filter, two-dimensional wavelet filter, maximum and minimum filter are used to eliminate the salt & pepper noise of image. Then we analysis and compare the results of the five methods to find the best way to eliminate the image noise.

scholarly journals Application of Different Filtering Techniques in Digital Image Processing

2021 ◽  
Vol 2062 (1) ◽  
pp. 012007
Author(s):  
Sumant Sekhar Mohanty ◽  
Sushreeta Tripathy
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Noise ◽  
Noise Model ◽  
Electronic Noise ◽  
Original Image ◽  
Color Information ◽  
Processing Steps ◽  
Filtering Techniques

Abstract Noise in an image is a random variation of brightness or color information in the original image. Noise is consistently presented in digital images during picture obtaining, coding, transmission, and processing steps. Image noise is most apparent in image regions with a low signal level. There are various reasons for the creation of noise in an image, such as electronic noise in amplifiers or detectors, disturbances and overheating of the sensor, disturbances in the medium of traveling for a digital image, etc. Noise is exceptionally hard to eliminate from the digital pictures without the earlier information of the noise model. There are various types of noise that can be available in a noise model. Filters are used to remove these types of noises in a digital image in image processing. In this research, we have implemented different filtering techniques that have been used to remove the noises in an image.

Applied-Information Technology with Method of Digital Image Noise Processing

2014 ◽  
Vol 951 ◽  
pp. 253-256 ◽  
Author(s):  
Guo Qing Yu ◽  
Chen Meng Sui ◽  
Bing Dong Sui
Keyword(s):  
Image Processing ◽  
Information Technology ◽  
Digital Image Processing ◽  
Digital Image ◽  
Average Method ◽  
Image Noise ◽  
Computer Algorithm ◽  
Basic Knowledge ◽  
Median Filtering ◽  
Low Pass

Digital image processing is a kind of technology which employs a certain algorithm to realize image processing through computer algorithm. The powerful capacity of computing and graphics displaying function of Matlab makes image processing becomes more simple and intuitive. This paper introduces the basic knowledge of dealing with noise in digital image, expounds the neighborhood average method, median filtering in detail, and low pass filtering and other typical of eliminating noise method , and at the same time analyzes and compares the characteristics of several typical methods by use of the software Matlab.

scholarly journals Radiopacity of Methacrylate and Silorane Composite Resins Using a Digital Radiographic System

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Leily Macedo Firoozmand ◽  
Mariana Gonçalves Cordeiro ◽  
Marcos André dos Santos Da Silva ◽  
Rudys Rodolfo De Jesus Tavarez ◽  
Etevaldo Matos Maia Filho
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Equivalent Width ◽  
Composite Resins ◽  
Digital Method ◽  
Human Tooth ◽  
Resin Composites ◽  
Mean Values ◽  
The Mean

The aim of this study was to evaluate the radiopacity of silorane and methacrylate resin composites, comparing them to the enamel, dentin, and aluminum penetrometer using a digital image. From six resin composites (Filtek™P90, Filtek Z350, Filtek Z350 XT flow, Tetric Ceram, TPH Spectrum, and SureFil SDR flow) cylindrical disks (5 × 1 mm) were made and radiographed by a digital method, together with a 15-step aluminum step-wedge and a 1 mm slice of human tooth. The degree of radiopacity of each image was quantified using digital image processing. The mean values of the shades of gray of the tested materials were measured and the equivalent width of aluminum was calculated for each resin. The results of our work yielded the following radiopacity values, given here in descending order: Tetric Ceram > TPH > SDR > Z350 > Z350 flow > P90 > enamel > dentin. The radiopacity of the materials was different both for the enamel and for the dentin, except for resin P90, which was no different than enamel. In conclusion, silorane-based resin exhibited a radiopacity higher than dentin and closest to the enamel; a large portion of the methacrylate-based flow and conventional resins demonstrated greater radiopacity in comparison to dentin and enamel.

Relationship between Clothing Pressure and Fabric Tension

2011 ◽  
Vol 175-176 ◽  
pp. 797-800
Author(s):  
Zhi Ge Chen ◽  
Qing Guan Chen
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
The Body ◽  
Clothing Pressure ◽  
The Relationship

The clothing shape will be changed when a wearer moves or changes his pose. The clothing pressure which acts on the body will be varied according to these changes of clothing shape. In this paper, the changes of clothing shape, the tension of fabric, the clothing pressure on body will be measured. The Digital image processing will be used to measure the changes of fabric shape. The relationship between the changes of clothing shape and the fabric tension, between the fabric tension and the clothing pressure on body will be discussed.

An Overview of Digital Image Processing and Recognition (Invited Paper)

1982 ◽  
Vol 40 ◽  
pp. 700-702
Author(s):  
R. C. Gonzalez
Keyword(s):  
Image Processing ◽  
New York ◽  
Digital Image Processing ◽  
Digital Image ◽  
Practical Implementation ◽  
Submarine Cable ◽  
Vigorous Growth ◽  
Digitized Pictures ◽  
Processing Techniques ◽  
And Storage

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.

A method to measure pores and fissures in geologic materials under S.E.M. by digital image processing

1978 ◽  
Vol 36 (1) ◽  
pp. 212-213
Author(s):  
L. Montoto ◽  
M. Montoto ◽  
A. Bel-Lan
Keyword(s):  
Image Processing ◽  
Optical Microscopy ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Processing ◽  
Free Surfaces ◽  
Geologic Materials ◽  
Automatic Information ◽  
Detector Output ◽  
Rock Specimens

INTRODUCTION.- The physical properties of rock masses are greatly influenced by their internal discontinuities, like pores and fissures. So, these need to be measured as a basis for interpretation. To avoid the basic difficulties of measurement under optical microscopy and analogic image systems, the authors use S.E.M. and multiband digital image processing. In S.E.M., analog signal processing has been used to further image enhancement (1), but automatic information extraction can be achieved by simple digital processing of S.E.M. images (2). The use of multiband image would overcome difficulties such as artifacts introduced by the relative positions of sample and detector or the typicals encountered in optical microscopy.DIGITAL IMAGE PROCESSING.- The studied rock specimens were in the form of flat deformation-free surfaces observed under a Phillips SEM model 500. The SEM detector output signal was recorded in picture form in b&w negatives and digitized using a Perkin Elmer 1010 MP flat microdensitometer.

Digital image processing methods applied to the study of annealing time on semiconductor-metal eutectic composites

1988 ◽  
Vol 46 ◽  
pp. 848-849
Author(s):  
J. Hefter
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Electronic Device ◽  
Processing System ◽  
Average Diameter ◽  
Eutectic Solidification ◽  
Metal Silicide ◽  
The Matrix ◽  
Microscopic Studies

Semiconductor-metal composites, formed by the eutectic solidification of silicon and a metal silicide have been under investigation for some time for a number of electronic device applications. This composite system is comprised of a silicon matrix containing extended metal-silicide rod-shaped structures aligned in parallel throughout the material. The average diameter of such a rod in a typical system is about 1 μm. Thus, characterization of the rod morphology by electron microscope methods is necessitated.The types of morphometric information that may be obtained from such microscopic studies coupled with image processing are (i) the area fraction of rods in the matrix, (ii) the average rod diameter, (iii) an average circularity (roundness), and (iv) the number density (Nd;rods/cm2). To acquire electron images of these materials, a digital image processing system (Tracor Northern 5500/5600) attached to a JEOL JXA-840 analytical SEM has been used.

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