Affine Texture Analysis with Scale-Area Histogram

2011 ◽  
Vol 474-476 ◽  
pp. 1183-1186
Author(s):  
Qiang Song
Keyword(s):  
Texture Analysis ◽  
Real World ◽  
Spatial Scales ◽  
Texture Feature ◽  
Scale Analysis ◽  
Visual Appearance ◽  
The Real ◽  
Multi Scale ◽  
Analysis Measurement ◽  
Orientation Scale

A major problem of texture analysis is that textures in the real world are often not uniform due to variations in orientation, scale, or other visual appearance. In this paper, affine texture analysis with texel scale-area histogram is presented. A textural image is decomposed into a set of scale images and each scale image consists of square texels of the same size. The scale-area histogram of texel is used as texture feature for multi-scale texture analysis and dominant texture scale analysis. Measurement of the dominant texel sizes of textural images with different rotation angles and spatial scales indicates that rotational and scaled transformations of textural image result in the motion of translation in scale-area histogram.

scholarly journals Boreal river impoundments caused little change in fish diversity but clear community assemblage shifts: A multi-scale analysis

2017 ◽  
Author(s):  
Katrine Turgeon ◽  
Christian Turpin ◽  
Irene Gregory-Eaves
Keyword(s):  
Beta Diversity ◽  
Spatial Scales ◽  
Fish Diversity ◽  
Sampling Station ◽  
List Type ◽  
Species Assemblage ◽  
Scale Analysis ◽  
Multi Scale ◽  
Boreal River ◽  
Multi Scale Analysis

AbstractHydroelectricity is often presented as a clean and renewable energy source, but river flow regulation and fragmentation caused by dams are recognized to impact aquatic biodiversity in temperate and tropical ecosystems. However, the effects of boreal river impoundment are not clear as the few studies that exist have not been able to separate the hydrological changes brought about by dams from other factors (e.g. fish stocking, and species introduction).We adopted a multi-scale analysis to examine changes in nearshore fish communities over 20 years (spanning before and after impoundment) using a network of 24 sampling stations spread across from four reservoirs and two hydroelectricity complexes located in the boreal region (Northern Québec, Canada). Given the remote location, confounding factors were minimal.We found no strong temporal trends in alpha- and gamma-diversity in impacted stations (upstream and downstream of the dam) relative to reference sites across the three spatial scales. Using beta-diversity analyses, we also detected a high stability in fish composition over time and space at the complex and reservoir scales.At the scale of the sampling stations, we observed higher rates of species turnover (beta-diversity) coincident with the time of reservoir filling and shortly after. Likewise, we detected species assemblage shifts that correlated with time since impoundment only at the sampling station scale. This pattern was masked at the complex and reservoir scales.Synthesis and applications. Overall, the isolated effect of impoundment in these remote boreal ecosystems caused no loss of species and little change in fish diversity over 20 years, but resulted in substantial species assemblage shifts. Our work shows that examining community data at different scales is key to understand the anthropogenic impacts on fish biodiversity.

scholarly journals Canopy Height Estimation from Single Multispectral 2D Airborne Imagery Using Texture Analysis and Machine Learning in Structurally Rich Temperate Forests

2019 ◽  
Vol 11 (23) ◽  
pp. 2853
Author(s):  
Christos Boutsoukis ◽  
Ioannis Manakos ◽  
Marco Heurich ◽  
Anastasios Delopoulos
Keyword(s):  
Land Cover ◽  
Texture Analysis ◽  
Spatial Scales ◽  
Computational Cost ◽  
Texture Feature ◽  
Cost Effective ◽  
Canopy Height ◽  
Support Vector ◽  
Structural Parameter ◽  
Wide Range

Canopy height is a fundamental biophysical and structural parameter, crucial for biodiversity monitoring, forest inventory and management, and a number of ecological and environmental studies and applications. It is a determinant for linking the classification of land cover to habitat categories towards building one-to-one relationships. Light detection and ranging (LiDAR) or 3D Stereoscopy are the commonly used and most accurate remote sensing approaches to measure canopy height. However, both require significant time and budget resources. This study proposes a cost-effective methodology for canopy height approximation using texture analysis on a single 2D image. An object-oriented approach is followed using land cover (LC) map as segmentation vector layer to delineate landscape objects. Global texture feature descriptors are calculated for each land cover object and used as variables in a number of classifiers, including single and ensemble trees, and support vector machines. The aim of the analysis is the discrimination among classes in a wide range of height values used for habitat mapping (from less than 5 cm to 40 m). For that task, different spatial resolutions are tested, representing a range from airborne to spaceborne quality ones, as well as their combinations, forming a multiresolution training set. Multiple dataset alternatives are formed based on the missing data handling, outlier removal, and data normalization techniques. The approach was applied using orthomosaics from DMC II airborne images, and evaluated against a reference LiDAR-derived canopy height model (CHM). Results reached overall object-based accuracies of 67% with the percentage of total area correctly classified exceeding 88%. Sentinel-2 simulation and multiresolution analysis (MRA) experiments achieved even higher accuracies of up to 85% and 91%, respectively, at reduced computational cost, showing potential in terms of transferability of the framework to large spatial scales.

Fast Gabor Filterbank and its Application in Fingerprint Texture Analysis

2012 ◽  
Vol 466-467 ◽  
pp. 1295-1299
Author(s):  
Yu Jun Zhang ◽  
Miao Yu ◽  
Wan Tong Zhao ◽  
Yang Xu
Keyword(s):  
Computational Complexity ◽  
Texture Analysis ◽  
Gabor Filter ◽  
Texture Feature ◽  
Fingerprint Recognition ◽  
Fingerprint Identification ◽  
Main Method ◽  
The Real

Minutiae-based matching is the main method of fingerprint recognition. Anil K. Jain brought forward a method (FingerCode) which use Gabor filter to extract the texture feature of fingerprint and match it. In order to get a faster algorithm of fingerprint identification, the properties of the real part of Gabor filter are analyzed and the Gabor filter algorithm is accelerated in special conditions and is validated by experiment, which decreases the computational complexity from O(n2) to O(n).

Current Issues: Evidence-Based Practice for the Real World: Thoughts on Clinical Education in Communication Disorders

2010 ◽  
Vol 20 (3) ◽  
pp. 100-105 ◽  
Author(s):  
Anne K. Bothe
Keyword(s):  
Clinical Education ◽  
Real World ◽  
Evidence Based Practice ◽  
Communication Disorders ◽  
University Faculty ◽  
Evidence Based ◽  
Speech Language Pathology ◽  
Basic Principles ◽  
The Real ◽  
Language Pathology

This article presents some streamlined and intentionally oversimplified ideas about educating future communication disorders professionals to use some of the most basic principles of evidence-based practice. Working from a popular five-step approach, modifications are suggested that may make the ideas more accessible, and therefore more useful, for university faculty, other supervisors, and future professionals in speech-language pathology, audiology, and related fields.

The Real-World Fellowship

2006 ◽  
Vol 40 (7) ◽  
pp. 47
Author(s):  
LEE SAVIO BEERS
Keyword(s):  
Real World ◽  
The Real

Contracts in the Real World

2016 ◽  
Author(s):  
Lawrence A. Cunningham
Keyword(s):  
Real World ◽  
The Real
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