scholarly journals Shape Recognition Based on Projected Edges and Global Statistical Features

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Attila Stubendek ◽  
Kristóf Karacs
Keyword(s):  
Shape Descriptor ◽  
Statistical Features ◽  
Global Features ◽  
Filter Model ◽  
Second Stage ◽  
Edge Based ◽  
Independent Features ◽  
Local Edge ◽  
Nearest Neighborhood ◽  
Neighborhood Type

A combined shape descriptor for object recognition is presented, along with an offline and online learning method. The descriptor is composed of a local edge-based part and global statistical features. We also propose a two-level, nearest neighborhood type multiclass classification method, in which classes are bounded, defining an inherent rejection region. In the first stage, global features are used to filter model instances, in contrast to the second stage, in which the projected edge-based features are compared. Our experimental results show that the combination of independent features leads to increased recognition robustness and speed. The core algorithms map easily to cellular architectures or dedicated VLSI hardware.

scholarly journals OBJECT CONTOUR COMPLETION BY COMBINING OBJECT RECOGNITION AND LOCAL EDGE CUES

2017 ◽  
Author(s):  
Kar Seng Loke
Keyword(s):  
Optimization Procedure ◽  
Specific Information ◽  
Top Down ◽  
Bottom Up ◽  
Object Contour ◽  
Contour Feature ◽  
Edge Based ◽  
Local Edge ◽  
Initial Object ◽  
Contour Completion

We developed a top-down and bottom-up segmentation ofobjects using shape contours through a two-stage procedure. First, the object was identified using an edge-based contour feature and then the object contour was obtained using a constraint optimization procedure based on the results from the earlier identified contours. The initial object detection provides object category specific information for the contour completion to be effected. We argue that top-down bottom-up interaction architecture has plausible neurological correlates. This method has an advantage in that it does not require learning boundaries with large datasets.  

scholarly journals A Modified Approach of Extracting Landfast Ice Edge Based on Sentinel-1A InSAR Coherence Image in the Gulf of Bothnia

2021 ◽  
Vol 9 (10) ◽  
pp. 1076
Author(s):  
Zhiyong Wang ◽  
Zihao Wang ◽  
Hao Li ◽  
Ping Ni ◽  
Jian Liu
Keyword(s):  
Median Filter ◽  
Reference Method ◽  
Radar Data ◽  
Landfast Ice ◽  
Gulf Of Bothnia ◽  
Ice Edge ◽  
Image Pairs ◽  
Edge Based ◽  
The Baltic ◽  
Local Edge

Landfast ice is an integral component of the coastal ecosystem. Extracting the edge and mapping the extent of landfast ice are one of the main methods for studying ice changes. In this work, a standardized process for extracting landfast ice edge in the Baltic Sea using the InSAR coherence image is established with Sentinel-1 radar data and InSAR technology. A modified approach combining multiscale segmentation and morphological erosion is then proposed to provide a reliable way to extract landfast ice edge. Firstly, the coherence image is obtained using InSAR technology. Then, the edge is separated and extracted with the modified approach. The modified approach is essentially a four-step procedure involving image segmentation, median filter, morphological erosion, and rejection of small patches. Finally, the full extent of landfast ice can be obtained using floodfill algorithm. Multiple InSAR image pairs of Sentinel-1A acquired from 2018 to 2019 are utilized to successfully extract the landfast ice edge in the Gulf of Bothnia. The results show that the landfast ice edge and the extents obtained by the proposed approach are visually consistent with those shown in the ice chart issued by the Swedish Meteorological and Hydrological Institute (SMHI) over a coastline length of 345 km. The mean distance between land–water boundary and the coastline issued by the National Oceanic and Atmospheric Administration (NOAA) is 109.1 m. The modified approach obviously preserves more details in local edge than the reference method. The experimental results show that the modified approach proposed in this paper can extract the edge and map the extent of landfast ice more accurately and quickly, and is therefore expected to contribute to the further understanding and analyzing the changes of landfast ice in the future.

ANALYSIS OF ELECTROCARDIOGRAM SIGNALS OF ARRHYTHMIA AND ISCHEMIA USING FRACTAL AND STATISTICAL FEATURES

2013 ◽  
Vol 13 (01) ◽  
pp. 1350008 ◽  
Author(s):  
S. DON ◽  
DUCKWON CHUNG ◽  
DUGKI MIN ◽  
EUNMI CHOI
Keyword(s):  
Nearest Neighbor ◽  
State Of The Art ◽  
Gaussian Mixture ◽  
Statistical Features ◽  
K Nearest Neighbor ◽  
Second Stage ◽  
Electrocardiogram Signals ◽  
Third Stage ◽  
Electrocardiogram Ecg ◽  
Better Than

In this study, we present a three-stage method for detecting abnormalities and classifying electrocardiogram (ECG) beats using a k-nearest neighbor (k-NN) classifier and Gaussian mixture model (GMM). In the first stage, a signal filtering method is used to remove the ECG beat baseline wander. In the second stage, features are extracted based on Higuchi's fractal dimension (HFD) and statistical features. In the third stage, k-NN and GMM are used as classifiers to classify arrhythmia and ischemia. A total of 30,000 ECG segments obtained from the MIT-BIH Arrhythmia and European ST-T Ischemia databases were used to quantify this approach. 60% of the beats were used for training the classifier and the remaining 40%, for validating it. An overall accuracy of 99% and 98.24% was obtained for k-NN and GMM, respectively. This result is significantly better than that of currently used state-of-the-art classification approaches for arrhythmia and ischemia.

scholarly journals Network entropy using edge-based information functionals

2020 ◽  
Vol 8 (3) ◽  
Author(s):  
Furqan Aziz ◽  
Edwin R Hancock ◽  
Richard C Wilson
Keyword(s):  
Diffusion Process ◽  
Complex Networks ◽  
Structural Information ◽  
Structural Complexity ◽  
Network Models ◽  
Quantum Graph ◽  
Heat Diffusion ◽  
Graph Representation ◽  
Edge Based ◽  
Local Edge

Abstract In this article, we present a novel approach to analyse the structure of complex networks represented by a quantum graph. A quantum graph is a metric graph with a differential operator (including the edge-based Laplacian) acting on functions defined on the edges of the graph. Every edge of the graph has a length interval assigned to it. The structural information contents are measured using graph entropy which has been proved useful to analyse and compare the structure of complex networks. Our definition of graph entropy is based on local edge functionals. These edge functionals are obtained by a diffusion process defined using the edge-based Laplacian of the graph using the quantum graph representation. We first present the general framework to define graph entropy using heat diffusion process and discuss some of its properties for different types of network models. Second, we propose a novel signature to gauge the structural complexity of the network and apply the proposed method to different datasets.

Recognition of Optical Microscopy Images Based on Shape and Texture

2012 ◽  
Vol 195-196 ◽  
pp. 539-543
Author(s):  
Shu Heng Zhang ◽  
Wei Yang ◽  
Lian Yun Wang ◽  
Su Zhang
Keyword(s):  
Optical Microscopy ◽  
Airborne Pollen ◽  
Pollen Allergy ◽  
Pollen Grains ◽  
Texture Features ◽  
Shape Descriptor ◽  
Classification Rate ◽  
Occurrence Matrix ◽  
Nearest Neighborhood ◽  
Microscopy Images

Airborne pollen is the main cause of pollen allergy, so statistic of the amount and distribution of pollen in the air is important. This paper presents a method to identify airborne pollen grains in optical microscopy images. After pollen region is segmented by thresholding, global shape descriptor and Fourier descriptor are used to extract shape features, gray level co-occurrence matrix is employed to extract texture features, and finally pollen grains are classified by a k-nearest neighborhood classifier. In the experiment with 55 cases ofPoaceae, 44 cases ofMoraceaeand 48 cases ofPinaceae, a classification rate of 82.31% can be obtained with an accuracy of 85.45%, 61.36%, and 97.91% for each family.

Detecting soft shadows in a single outdoor image: From local edge-based models to global constraints

2014 ◽  
Vol 38 ◽  
pp. 310-319 ◽  
Author(s):  
Qi Dong ◽  
Yanli Liu ◽  
Qijun Zhao ◽  
Hongyu Yang
Keyword(s):  
Global Constraints ◽  
Soft Shadows ◽  
Edge Based ◽  
Local Edge

Altered Fine Structure of B Lymphocytes Correlated with Defective Terminal Differentiation

1973 ◽  
Vol 31 ◽  
pp. 386-387
Author(s):  
Dale E. Bockman ◽  
L. Y. Frank Wu ◽  
Alexander R. Lawton ◽  
Max D. Cooper
Keyword(s):  
Immune Deficiency ◽  
B Lymphocytes ◽  
Plasma Cells ◽  
Present Report ◽  
Specific Antigen ◽  
Terminal Differentiation ◽  
Second Stage ◽  
Two Stages ◽  
Deficiency Diseases ◽  
Cell Line Generation

B-lymphocytes normally synthesize small amounts of immunoglobulin, some of which is incorporated into the cell membrane where it serves as receptor of antigen. These cells, on contact with specific antigen, proliferate and differentiate to plasma cells which synthesize and secrete large quantities of immunoglobulin. The two stages of differentiation of this cell line (generation of B-lymphocytes and antigen-driven maturation to plasma cells) are clearly separable during ontogeny and in some immune deficiency diseases. The present report describes morphologic aberrations of B-lymphocytes in two diseases in which second stage differentiation is defective.

Cryomicroscopy of multiphase latices

1991 ◽  
Vol 49 ◽  
pp. 1060-1061
Author(s):  
O. L. Shaffer ◽  
M.S. El-Aasser ◽  
C. L. Zhao ◽  
M. A. Winnik ◽  
R. R. Shivers
Keyword(s):  
Electron Microscopy ◽  
Radiation Damage ◽  
Freeze Fracture ◽  
Particle Morphology ◽  
Second Stage ◽  
Transmission Electron ◽  
Important Approach ◽  
Carbon Coated ◽  
Preparation Techniques

Transmission electron microscopy is an important approach to the characterization of the morphology of multiphase latices. Various sample preparation techniques have been applied to multiphase latices such as OsO4, RuO4 and CsOH stains to distinguish the polymer phases or domains. Radiation damage by an electron beam of latices imbedded in ice has also been used as a technique to study particle morphology. Further studies have been developed in the use of freeze-fracture and the effect of differential radiation damage at liquid nitrogen temperatures of the latex particles embedded in ice and not embedded.Two different series of two-stage latices were prepared with (1) a poly(methyl methacrylate) (PMMA) seed and poly(styrene) (PS) second stage; (2) a PS seed and PMMA second stage. Both series have varying amounts of second-stage monomer which was added to the seed latex semicontinuously. A drop of diluted latex was placed on a 200-mesh Formvar-carbon coated copper grid.

Observations on the growth of barium bismuth oxide thin films

1992 ◽  
Vol 50 (1) ◽  
pp. 76-77
Author(s):  
M G. Norton ◽  
E.S. Hellman ◽  
E.H. Hartford ◽  
C.B. Carter
Keyword(s):  
Substrate Temperature ◽  
Deposition Process ◽  
Nucleation Layer ◽  
Second Stage ◽  
Device Applications ◽  
High Transition ◽  
Substrate Temperatures ◽  
Oriented Material ◽  
Barium Bismuth ◽  
Superconductor Device

The bismuthates (for example, Ba1-xKxBiO3) represent a class of high transition temperature superconductors. The lack of anisotropy and the long coherence length of the bismuthates makes them technologically interesting for superconductor device applications. To obtain (100) oriented Ba1-xKxBiO3 films on (100) oriented MgO, a two-stage deposition process is utilized. In the first stage the films are nucleated at higher substrate temperatures, without the potassium. This process appears to facilitate the formation of the perovskite (100) orientation on (100) MgO. This nucleation layer is typically between 10 and 50 nm thick. In the second stage, the substrate temperature is reduced and the Ba1-xKxBiO3 is grown. Continued growth of (100) oriented material is possible at the lower substrate temperature.

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