An adaptive-focus deformable model using statistical and geometric information

2000 ◽  
Vol 22 (8) ◽  
pp. 906-913 ◽  
Author(s):  
Dinggang Shen ◽  
C. Davatzikos
Keyword(s):  
Deformable Model ◽  
Geometric Information

On the Shape of Field-Ion Emitters

1976 ◽  
Vol 34 ◽  
pp. 520-521
Author(s):  
H.C. Eaton ◽  
B.N. Ranganathan ◽  
T.W. Burwinkle ◽  
R. J. Bayuzick ◽  
J.J. Hren
Keyword(s):  
Grain Boundary ◽  
Spherical Shape ◽  
Theoretical Strength ◽  
Evaporation Process ◽  
Field Evaporation ◽  
Geometric Information ◽  
Field Ion Microscopy ◽  
Considerable Error ◽  
True Shape ◽  
Ion Microscopy

The shape of the emitter is of cardinal importance to field-ion microscopy. First, the field evaporation process itself is closely related to the initial tip shape. Secondly, the imaging stress, which is near the theoretical strength of the material and intrinsic to the imaging process, cannot be characterized without knowledge of the emitter shape. Finally, the problem of obtaining quantitative geometric information from the micrograph cannot be solved without knowing the shape. Previously published grain-boundary topographies were obtained employing an assumption of a spherical shape (1). The present investigation shows that the true shape deviates as much as 100 Å from sphericity and boundary reconstructions contain considerable error as a result.Our present procedures for obtaining tip shape may be summarized as follows. An empirical projection, D=f(θ), is obtained by digitizing the positions of poles on a field-ion micrograph.

A Hybrid Approach for the Lung(s) Nodule Detection using the Deformable Model and Distance Transform

2020 ◽  
pp. -1--1
Author(s):  
Ayyaz Hussain ◽  
, Mohammed Alawairdhi ◽  
Fayez Alazemi ◽  
Sajid Khan ◽  
Muhammad Ramzan
Keyword(s):  
Hybrid Approach ◽  
Deformable Model ◽  
Distance Transform ◽  
Nodule Detection

scholarly journals Innovative techniques for the improvement of industrial noise sources identification by beamforming

Noise Mapping ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 129-137
Author(s):  
Giorgio Baldinelli ◽  
Francesco Bianchi ◽  
Danilo Costarelli ◽  
Francesco D’Alessandro ◽  
Flavio Scrucca ◽  
...  
Keyword(s):  
Image Processing ◽  
Noise Source ◽  
Focal Length ◽  
Noise Sources ◽  
Geometric Information ◽  
Industrial Noise ◽  
Sources Identification ◽  
Innovative Technique ◽  
Innovative Techniques

Abstract An innovative technique based on beamforming is implemented, at the aim of detecting the distances from the observer and the relative positions among the noise sources themselves in multisource noise scenarios. By means of preliminary activities to assess the optical camera focal length and stereoscopic measurements followed by image processing, the geometric information in the source-microphone direction is retrieved, a parameter generally missed in classic beamforming applications. A corollary of the method consists of the possibility of obtaining also the distance among different noise sources which could be present in a multisource environment. A loss of precision is found when the effect of the high acoustic reflectivity ground interferes with the noise source.

scholarly journals Orientation-Constrained System for Lamp Detection in Buildings Based on Computer Vision

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1516 ◽  
Author(s):  
Francisco Troncoso-Pastoriza ◽  
Pablo Eguía-Oller ◽  
Rebeca Díaz-Redondo ◽  
Enrique Granada-Álvarez ◽  
Aitor Erkoreka
Keyword(s):  
Computer Vision ◽  
Optimization Methods ◽  
Geometric Information ◽  
Constrained System ◽  
Building Information Modelling ◽  
Correct Model ◽  
Reprojection Error ◽  
Localization Errors ◽  
Building Information ◽  
Error Filtering

Computer vision is used in this work to detect lighting elements in buildings with the goal of improving the accuracy of previous methods to provide a precise inventory of the location and state of lamps. Using the framework developed in our previous works, we introduce two new modifications to enhance the system: first, a constraint on the orientation of the detected poses in the optimization methods for both the initial and the refined estimates based on the geometric information of the building information modelling (BIM) model; second, an additional reprojection error filtering step to discard the erroneous poses introduced with the orientation restrictions, keeping the identification and localization errors low while greatly increasing the number of detections. These enhancements are tested in five different case studies with more than 30,000 images, with results showing improvements in the number of detections, the percentage of correct model and state identifications, and the distance between detections and reference positions.

scholarly journals Conditional-mean initialization using neighboring objects in deformable model segmentation

2008 ◽  
Author(s):  
Ja-Yeon Jeong ◽  
Joshua V. Stough ◽  
J. Steve Marron ◽  
Stephen M. Pizer
Keyword(s):  
Deformable Model ◽  
Conditional Mean ◽  
Model Segmentation
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