Detection of Blobs Using Variable Windows

1995 ◽  
Vol 7 (5) ◽  
pp. 404-409
Author(s):  
Machi Saitoh ◽  
◽  
Hiroshi Katsulai ◽  
Keyword(s):  
Image Analysis ◽  
Simple Method ◽  
Blob Detection ◽  
Compact Region ◽  
Wide Range ◽  
Variable Window ◽  
Size Variable

A blob is a compact region in the image which is surrouded by a smoothly curved closed edge and, at the same time, is lighter or darker than the background. Many objects which are found in an image can be viewed as blobs. It is very important to quickly detect in an image the location of blobs for a wide range of applications of image analysis. In this paper, we propose a noniterative simple method of blob detection which is applicable to various forms of blobs by scanning an image with a size variable window, and does not require so much memory and time for computations because of its simplicity, and demonstrate its effectiveness through experiments.

scholarly journals Image Segmentation and Object-Based Image Analysis for Environmental Monitoring: Recent Areas of Interest, Researchers’ Views on the Future Priorities

2020 ◽  
Vol 12 (11) ◽  
pp. 1772
Author(s):  
Brian Alan Johnson ◽  
Lei Ma
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Image Segmentation ◽  
Online Survey ◽  
Accuracy Assessment ◽  
Learning Approaches ◽  
Special Issue ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Wide Range

Image segmentation and geographic object-based image analysis (GEOBIA) were proposed around the turn of the century as a means to analyze high-spatial-resolution remote sensing images. Since then, object-based approaches have been used to analyze a wide range of images for numerous applications. In this Editorial, we present some highlights of image segmentation and GEOBIA research from the last two years (2018–2019), including a Special Issue published in the journal Remote Sensing. As a final contribution of this special issue, we have shared the views of 45 other researchers (corresponding authors of published papers on GEOBIA in 2018–2019) on the current state and future priorities of this field, gathered through an online survey. Most researchers surveyed acknowledged that image segmentation/GEOBIA approaches have achieved a high level of maturity, although the need for more free user-friendly software and tools, further automation, better integration with new machine-learning approaches (including deep learning), and more suitable accuracy assessment methods was frequently pointed out.

Measuring Coral Skeletal Architecture Using Image Analysis v1

2021 ◽  
Author(s):  
Rowan Mclachlan ◽  
Ashruti Patel ◽  
Andrea G Grottoli
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Image Analysis ◽  
Scleractinian Coral ◽  
Coral Species ◽  
Energy Materials ◽  
Simple Method ◽  
Coral Skeletons ◽  
Skeletal Structures ◽  
Scanning Electron

Coral morphology is influenced by genetics, the environment, or the interaction of both, and thus is highly variable. This protocol outlines a non-destructive and relatively simple method for measuring Scleractinian coral sub-corallite skeletal structures (such as the septa length, theca thickness, and corallite diameter, etc.) using digital images produced as a result of digital microscopy or from scanning electron microscopy. This method uses X and Y coordinates of points placed onto photomicrographs to automatically calculate the length and/or diameter of a variety of sub-corallite skeletal structures in the Scleractinian coral Porites lobata. However, this protocol can be easily adapted for other coral species - the only difference may be the specific skeletal structures that are measured (for example, not all coral species have a pronounced columella or pali, or even circular corallites). This protocol is adapted from the methods described in Forsman et al. (2015) & Tisthammer et al. (2018). There are 4 steps to this protocol: 1) Removal of Organic Tissue from Coral Skeletons 2) Imaging of Coral Skeletons 3) Photomicrograph Image Analysis 4) Calculation of Corallite Microstructure Size This protocol was written by Dr. Rowan McLachlan and was reviewed by Ashruti Patel and Dr. Andréa Grottoli. Acknowledgments Leica DMS 1000 and Scanning Electron Microscopy photomicrographs used in this protocol were acquired at the Subsurface Energy Materials Characterization and Analysis Laboratory (SEMCAL), School of Earth Sciences at The Ohio State University, Ohio, USA. I would like to thank Dr. Julie Sheets, Dr. Sue Welch, and Dr. David Cole for training me on the use of these instruments.

scholarly journals Automatic and Online Detection of Rotor Fault State

2018 ◽  
Vol 7 (1) ◽  
pp. 43 ◽  
Author(s):  
Ali Ouanas ◽  
Ammar Medoued ◽  
Salim Haddad ◽  
Mourad Mordjaoui ◽  
D. Sayad
Keyword(s):  
Induction Motor ◽  
Dimensional Space ◽  
Operating Conditions ◽  
Online Detection ◽  
K Nearest Neighbor ◽  
Simple Method ◽  
Important Place ◽  
Motor Test ◽  
Wide Range ◽  
Fault State

In this work, we propose a new and simple method to insure an online and automatic detection of faults that affect induction motor rotors. Induction motors now occupy an important place in the industrial environment and cover an extremely wide range of applications. They require a system installation that monitors the motor state to suit the operating conditions for a given application. The proposed method is based on the consideration of the spectrum of the single-phase stator current envelope as input of the detection algorithm. The characteristics related to the broken bar fault in the frequency domain extracted from the Hilbert Transform is used to estimate the fault severity for different load levels through classification tools. The frequency analysis of the envelope gives the frequency component and the associated amplitude which define the existence of the fault. The clustering of the indicator is chosen in a two-dimensional space by the fuzzy c mean clustering to find the center of each class. The distance criterion, the K-Nearest Neighbor (KNN) algorithm and the neural networks are used to determine the fault type. This method is validated on a 5.5-kW induction motor test bench.Article History: Received July 16th 2017; Received: October 5th 2017; Accepted: Januari 6th 2018; Available onlineHow to Cite This Article: Ouanas, A., Medoued, A., Haddad, S., Mordjaoui, M., and Sayad, D. (2017) Automatic and online Detection of Rotor Fault State. International Journal of Renewable Energy Development, 7(1), 43-52.http://dx.doi.org/10.14710/ijred.7.1.43-52

Simplified approach to confidence limited in radioimmunassay.

1980 ◽  
Vol 26 (6) ◽  
pp. 763-765 ◽  
Author(s):  
R C Baxter
Keyword(s):  
Quality Control ◽  
Mean Value ◽  
Confidence Limits ◽  
Simple Method ◽  
Response Variable ◽  
Simplified Approach ◽  
Quadratic Curve ◽  
Wide Range ◽  
Advanced Computing ◽  
Routine Quality Control

Abstract A simple method of calculating confidence limits for radioimmunoassay data is presented. The method involves the use of the within-assay variation in dose estimate of three routine quality-control specimens, measured in repeated assays, to estimate the confidence limits for results on unknown samples. Results for control specimens are combined by calculating the unique quadratic curve fitting a graph of within-assay standard deviation vs mean value for each control. This method requires no special data accumulation or advanced computing equipment. For cortisol, lutropin, and thyroxine radioimmunoassays, confidence limits calculated in this way have been compared with those calculated from the variance of the response variable “B/B0” in repeated standard curves. Both methods agree well with actual limits observed when plasma pools containing a wide range of hormone concentrations are assayed repeatedly.

scholarly journals Obituary: Georges Matheron

2000 ◽  
Vol 32 (4) ◽  
pp. 1190-1192
Author(s):  
Dominique Jeulin
Keyword(s):  
Image Analysis ◽  
Image Coding ◽  
Scientific Community ◽  
Random Media ◽  
Applied Mathematics ◽  
Artificial Vision ◽  
Scientific Heritage ◽  
Wide Range ◽  
Analysis And Synthesis ◽  
Major Figure

The scientific community is saddened to learn of the death of Professor Georges Matheron on 7 August 2000. As a major figure in applied mathematics over four decades, he leaves an outstanding scientific heritage, covering a wide range of domains where probabilistic tools and models are implemented. He also trained more than one generation of researchers, engineers and teachers. In the fields of theoretical and applied random media and image analysis his work has inspired many researchers worldwide: mathematicians, statisticians, physicists, experimentalists, earth scientists, mining engineers and also users of image analysis and synthesis in all its applications (materials, biology, artificial vision, CAD, remote sensing, geophysics, biometry, image coding etc.).

scholarly journals Pore system changes of damaged Brazilian oxisols and nitosols induced by wet-dry cycles as seen in 2-D micromorphologic image analysis

2009 ◽  
Vol 81 (1) ◽  
pp. 151-161 ◽  
Author(s):  
Luiz F. Pires ◽  
Klaus Reichardt ◽  
Miguel Cooper ◽  
Fabio A.M. Cássaro ◽  
Nivea M.P. Dias ◽  
...  
Keyword(s):  
Image Analysis ◽  
Size Distribution ◽  
Soil Structure ◽  
Tropical Soils ◽  
Transport Processes ◽  
Structure Characterization ◽  
Control Treatment ◽  
Simple Method ◽  
Wetting And Drying ◽  
Essential Information

Soil pore structure characterization using 2-D image analysis constitutes a simple method to obtain essential information related to soil porosity and pore size distribution (PSD). Such information is important to infer on soil quality, which is related to soil structure and transport processes inside the soil. Most of the time soils are submitted to wetting and drying cycles (W-D), which can cause important changes in soils with damaged structures. This report uses 2-D image analysis to evaluate possible modifications induced by W-D cycles on the structure of damaged soil samples. Samples of three tropical soils (Geric Ferralsol, GF; Eutric Nitosol, EN; and Rhodic Ferralsol, RF) were submitted to three treatments: 0WD, the control treatment in which samples were not submitted to any W-D cycle; 3WD and 9WD with samples submitted to 3 and 9 consecutive W-D cycles, respectively. It was observed that W-D cycles produced significant changes in large irregular pores of the GF and RF soils, and in rounded pores of the EN soil. Nevertheless, important changes in smaller pores (35, 75, and 150 µm) were also observed for all soils. As an overall consideration, it can be said that the use of image analysis helped to explain important changes in soil pore systems (shape, number, and size distribution) as consequence of W-D cycles.

scholarly journals A Very Simple Method for Quickly Making Large Numbers of Measurements on Micrographs

2009 ◽  
Vol 17 (3) ◽  
pp. 50-53
Author(s):  
Ron Anderson
Keyword(s):  
Thin Film ◽  
Grain Size ◽  
Image Analysis ◽  
Integrated Circuit ◽  
Ceramic Substrate ◽  
Raw Material ◽  
Material Particle ◽  
Simple Method ◽  
Plan View ◽  
Large Computer

It has been in the back of my mind to write this up for MT since I retired from a certain large computer company. Inasmuch as Paul's article above is a perfect lead-in, there is no time like the present. Our lab supported a semiconductor integrated circuit and a ceramic substrate manufacturing facility. We were continually required to measure circuit line widths on plan-view specimens and layer thicknesses on cross-section specimens for both semiconductor and ceramic substrate specimens and we were often asked to determine thin film grain size and ceramic raw material particle size data. A large number of measurements were required for each specimen to guarantee statistically sound data. We had image analysis software available that we used whenever we could, but often found that measuring things on a system using grey-level image analysis as input simply did not work. This is especially true for thin film grain size determination when using diffraction contrast TEM images for input.

scholarly journals Glass-on-Glass Fabrication of Bottle-Shaped Tunable Microlasers and their Applications

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jonathan M. Ward ◽  
Yong Yang ◽  
Síle Nic Chormaic
Keyword(s):  
Gas Flow ◽  
60 Ghz ◽  
Melting Points ◽  
Simple Method ◽  
Flow Sensitivity ◽  
Whispering Gallery ◽  
Wide Range ◽  
Novel Method ◽  
Doped Glass ◽  
Lasing Modes

Abstract We describe a novel method for making microbottle-shaped lasers by using a CO2 laser to melt Er:Yb glass onto silica microcapillaries or fibres. This is realised by the fact that the two glasses have different melting points. The CO2 laser power is controlled to flow the doped glass around the silica cylinder. In the case of a capillary, the resulting geometry is a hollow, microbottle-shaped resonator. This is a simple method for fabricating a number of glass whispering gallery mode (WGM) lasers with a wide range of sizes on a single, micron-scale structure. The Er:Yb doped glass outer layer is pumped at 980 nm via a tapered optical fibre and WGM lasing is recorded around 1535 nm. This structure facilitates a new way to thermo-optically tune the microlaser modes by passing gas through the capillary. The cooling effect of the gas flow shifts the WGMs towards shorter wavelengths and thermal tuning of the lasing modes over 70 GHz is achieved. Results are fitted using the theory of hot wire anemometry, allowing the flow rate to be calibrated with a flow sensitivity as high as 72 GHz/sccm. Strain tuning of the microlaser modes by up to 60 GHz is also demonstrated.

The longest common substring problem

2015 ◽  
Vol 27 (2) ◽  
pp. 277-295 ◽  
Author(s):  
MAXIME CROCHEMORE ◽  
COSTAS S. ILIOPOULOS ◽  
ALESSIO LANGIU ◽  
FILIPPO MIGNOSI
Keyword(s):  
Data Structures ◽  
Dna Sequences ◽  
Simple Algorithm ◽  
Suffix Trees ◽  
Simple Method ◽  
Suffix Arrays ◽  
Lowest Common Ancestor ◽  
Wide Range ◽  
Efficient Data ◽  
Longest Common Substring

Given a set $\mathcal{D}$ of q documents, the Longest Common Substring (LCS) problem asks, for any integer 2 ⩽ k ⩽ q, the longest substring that appears in k documents. LCS is a well-studied problem having a wide range of applications in Bioinformatics: from microarrays to DNA sequences alignments and analysis. This problem has been solved by Hui (2000International Journal of Computer Science and Engineering15 73–76) by using a famous constant-time solution to the Lowest Common Ancestor (LCA) problem in trees coupled with the use of suffix trees.In this article, we present a simple method for solving the LCS problem by using suffix trees (STs) and classical union-find data structures. In turn, we show how this simple algorithm can be adapted in order to work with other space efficient data structures such as the enhanced suffix arrays (ESA) and the compressed suffix tree.

Sign in / Sign up

Export Citation Format

Share Document