scholarly journals Digital Image Processing based Surface Area Calculation

2020 ◽  
Vol 10 (1) ◽  
pp. 186-190
Keyword(s):  
Image Processing ◽  
Surface Area ◽  
Digital Image Processing ◽  
Digital Image ◽  
Reference Object ◽  
Nondestructive Measurement ◽  
Actual Surface ◽  
Regular Shape ◽  
Object Based ◽  
Calculation System

The objective of current work is nondestructive measurement of surface area of regular or irregular shape just from image. Surface area calculation is mathematical part which needs to remember number of formulas and all for regular shape. It becomes more tedious if the shape whose area is to be calculated is irregular. In some cases such as mountain or lake measurement of dimension is also cumbersome task. To find the solution for such cases in today’s world of automation, the proposed work describes reference object based area calculation system which is based on different techniques of digital image processing. In this we have to click an image of object (whose area is to be calculated) along with one reference object with known surface area. Then the proposed system will perform image enhancement and segmentation operation and finally calculate the surface area of any 2-D surface. It is observed that the values obtained are having with good correlation with actual surface area values.

Turbidity Level Prediction Based on Suspended Particle Counting Through Image Processing Approach

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Temmy Wikaningrum ◽  
M. Galang Alvasa ◽  
Yandes Panelin ◽  
Rijal Hakiki
Keyword(s):  
Image Processing ◽  
Surface Water ◽  
Surface Area ◽  
Digital Image Processing ◽  
Digital Image ◽  
Drinking Water Treatment ◽  
Suspended Particles ◽  
Processing Approach ◽  
Pollutant Concentrations ◽  
Turbidity Level

Monitoring of pollutant concentrations in surface water becomes a concern, considering the utilization of surface water as the raw water for drinking water treatment plants (WTP). The fluctuation of pollutant concentrations in surface water can affect the performance of WTP. This research was conducted to assess the potential for turbidity level prediction based on the calculation of the number and surface area of suspended particles through a digital image processing approach. Measurements of the amount and surface area were carried out in the form of laboratory-scale experiments using the open source software ImageJ 1.46r. The algorithm in ImageJ can convert pixels into a number “value” and surface area through a series of digital image processing steps, henceforth compared with the existing measurement method. The results showed that there was a strong correlation between the number of particles and the concentration of formazine suspension (r = 0.9821), but does not apply to the surface area. Referring to the results of laboratory experiments, it can be concluded that the approach to measure the number of suspended particles can be the basis for predicting the turbidity level in the turbidity range 100-800 NTU, but does not apply to the turbidity range 0.02-20 NTU.

scholarly journals Method to Calculate the Surface Area of roots by Digital Image Processing

2019 ◽  
Author(s):  
Marcio Hosoya Name
Keyword(s):  
Image Processing ◽  
Surface Area ◽  
Digital Image Processing ◽  
Digital Image ◽  
Nutrient Management ◽  
Computational Method ◽  
Root Crops ◽  
Long Time ◽  
Soybean Roots ◽  
Java Platform

The evaluation of root crops is important for better understanding of the effects of plant nutrition and nutrient management in the soil. However, the studies and the root system of the culture are slow, require a long time and show low precision results. In this context, digital image processing can be an alternative. The objective of this study was to develop a computational method to assist in the evaluation of the surface area of ​​soybean roots. It was initially developed in Java platform by providing the OpenCV library through the plug-in JavaCV. Then, after the manual count, the soybean root samples that have been scanned, were loaded into the software. The software developed results were correlated with the intersection of the line method. The correlation coefficient (R = 0.77) obtained by the software developed was on average good, compared to the métododa line intersection. Therefore, in general, the proposed method was necessary paraestimar the surface area of ​​the soybean roots.

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.

Complementary Z-Contrast Imaging and Digital Image Processing

1985 ◽  
Vol 43 ◽  
pp. 304-305
Author(s):  
K. N. Colonna ◽  
G. Oliphant
Keyword(s):  
Image Processing ◽  
Heavy Metal ◽  
Digital Image Processing ◽  
Digital Image ◽  
Biological Tissue ◽  
Biological Imaging ◽  
Tissue Preparation ◽  
Contrast Imaging ◽  
Imaging Tool ◽  
Z Contrast

Harmonious use of Z-contrast imaging and digital image processing as an analytical imaging tool was developed and demonstrated in studying the elemental constitution of human and maturing rabbit spermatozoa. Due to its analog origin (Fig. 1), the Z-contrast image offers information unique to the science of biological imaging. Despite the information and distinct advantages it offers, the potential of Z-contrast imaging is extremely limited without the application of techniques of digital image processing. For the first time in biological imaging, this study demonstrates the tremendous potential involved in the complementary use of Z-contrast imaging and digital image processing.Imaging in the Z-contrast mode is powerful for three distinct reasons, the first of which involves tissue preparation. It affords biologists the opportunity to visualize biological tissue without the use of heavy metal fixatives and stains. For years biologists have used heavy metal components to compensate for the limited electron scattering properties of biological tissue.

Development of New Image Registration Techniques – A Research Framework

2018 ◽  
Vol 8 (3) ◽  
pp. 50
Author(s):  
Sindhu Madhuri G. ◽  
Indira Gandhi M P
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Digital Image Processing ◽  
Digital Image ◽  
Creative Thinking ◽  
Reference Image ◽  
Transformation Technique ◽  
Research Framework ◽  
Registration Process ◽  
Data Source

Image is a basic and fundamental data source for the digital image processing. This image data source is required to be processed into information or intelligence and further to knowledge levels where it is required to understand and migrate into knowledge economy systems. Image registration is one of such key and most important process already identified in the digital image processing domain. Image registration is a process of bringing the reference image and sensed image into a common co-ordinate system, and application of complex transformation techniques for necessary comparison of reference with sensed images obtained from different - views, times, spaces, etc., in order to extract the valuable information and intelligence embedded in them. Due to the complexity of overall image registration process, it is difficult to suggest a single transformation technique even for a specific application. In addition, it is highly impossible to suggest one single transformation technique for comparison of various sensed images with a reference image during the image registration process. This research gap calls for the development of new image registration techniques for the application of more than one transformation technique during the image registration process for the necessary comparisons with reference image & sensed images, those are obtained from the available heterogeneous sources or sensors, based on the requirement. In addition, it is a basic need to attempt for the measurement of effectiveness of the image registration process also. Therefore, a research framework is developed for image registration process and attempted for the measurement of its effectiveness also. This new research area is a novel idea, and is expected to emerge as a provision for the knowledge computations with creative thinking through the embedded intelligence extraction during the complex image registration process.

Sign in / Sign up

Export Citation Format

Share Document