scholarly journals Analysis of the effectiveness of constraining metrics of geometric simplification algorithms based on expert evaluation of line detail

2021 ◽  
Vol 27 (2) ◽  
pp. 253-267
Author(s):  
Timofey Samsonov ◽  
Olga Yakimova
Keyword(s):  
Hausdorff Distance ◽  
Numerical Estimate ◽  
Expert Evaluation ◽  
Effective Characteristic ◽  
Similar Reduction ◽  
Line Simplification ◽  
Survey Results ◽  
Number Of Bends ◽  
Modified Hausdorff Distance ◽  
Weighted Combination

The paper reveals dependencies between the character of the line shape and combination of constraining metrics that allows comparable reduction in detail by different geometric simplification algorithms. The study was conducted in a form of the expert survey. geometrically simplified versions of three coastline fragments were prepared using three different geometric simplification algorithms—Douglas-peucker, Visvalingam-Whyatt and Li-Openshaw. Simplification was constrained by similar value of modified hausdorff distance (linear offset) and similar reduction of number of line bends (compression of the number of detail elements). Respondents were asked to give a numerical estimate of the detail of each image, based on personal perception, using a scale from one to ten. The results of the survey showed that lines perceived by respondents as having similar detail can be obtained by different algorithms. however, the choice of the metric used as a constraint depends on the nature of the line. Simplification of lines that have a shallow hierarchy of small bends is most effectively constrained by linear offset. As the line complexity increases, the compression metric for the number of detail elements (bends) increases its influence in the perception of detail. For one of the three lines, the best result was consistently obtained with a weighted combination of the analyzed metrics as a constraint. None of the survey results showed that only reducing the number of bends can be used as an effective characteristic of similar reduction in detail. It was therefore found that the linear offset metric is more indicative when describing changes in line detail.

Binary Image Recognition Utilizing Computer Generated Templates

2017 ◽  
Author(s):  
Dustin Bielecki ◽  
Prakhar Jaiswal ◽  
Rahul Rai
Keyword(s):  
Image Recognition ◽  
Hausdorff Distance ◽  
Binary Image ◽  
Sorting Technique ◽  
Milling Operation ◽  
Modified Hausdorff Distance ◽  
Image Templates

This paper covers a method of taking images of physical parts which are then preprocessed and compared against CAD generated templates. A pseudo milling operation was performed on discretized points along CAD generated mill paths to create binary image templates. The computer-generated images were then tested against one another as a preliminarily sorting technique. This was done to reduce the number of sorting approaches used, by selecting the most reliable and discerning ones, and discarding the others. To apply the selected sorting methods for comparing CAD generated images and the images of physical parts, a translational and scaling normalization technique was implemented. Rotational variation occurs while scanning physical parts and it was addressed using two different techniques: first by determination of best rotation based on modified-Hausdorff distance (MHD); and second by comparing against all CAD based images for all template rotations. The proposed approach for automated sorting of physical parts was demonstrated by categorizing multiple geometries.

scholarly journals Methodology of expert evaluation of effectiveness of methods of organizational diagnostics

2017 ◽  
pp. 38-43
Author(s):  
T. V. CHIBIKOVA
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Random Variable ◽  
Diagnostic Methods ◽  
Practical Significance ◽  
Expert Evaluation ◽  
Practical Application ◽  
Actual Problem ◽  
Survey Results ◽  
Statistical Indicators

The article is devoted to the actual problem of assessing the effectiveness of consulting methods. Management consulting is a developing sphere of human activity. The technique of an estimation of efficiency of methods of organizational diagnostics is offered. The research was based on the problem of assessing the effectiveness of diagnostic methods in consulting using only economic indicators. According to the methodology, during the evaluation, the effectiveness of methods is is assessed in the light of costs and results, both should be similarly broken down into a number of elements. These elements were to be evaluated by experts. To confirm the validity of the results obtained, statistical indicators are used: variance of a random variable, standard deviation and coefficient of variation, which confirm (or disprove) the results of an expert poll.To approbate the methodology, a survey of experts elected among employees of consulting companies in Omsk was conducted. The survey data was analyzed. Based on the results of the analysis, the validity of the obtained survey results and the possibility of their practical application was concluded. The practical significance of the study is that it is possible to apply the methodology of interviewing experts in practice. The purpose of such surveys will be a regular reassessment and identification of the need for specific consulting methods for certain methods of organizational diagnostics.

scholarly journals Fully automatic segmentation of bee wing images

2020 ◽  
Vol 12 (2) ◽  
pp. 37-45
Author(s):  
João Marcos Garcia Fagundes ◽  
Allan Rodrigues Rebelo ◽  
Luciano Antonio Digiampietri ◽  
Helton Hideraldo Bíscaro
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Feature Extraction ◽  
Hausdorff Distance ◽  
Automatic Segmentation ◽  
Food Crops ◽  
Artificial Intelligence Techniques ◽  
Fully Automatic ◽  
Modified Hausdorff Distance ◽  
F Measure

Bee preservation is important because approximately 70% of all pollination of food crops is made by them and this service costs more than $ 65 billion annually. In order to help this preservation, the identification of the bee species is necessary, and since this is a costly and time-consuming process, techniques that automate and facilitate this identification become relevant. Images of bees' wings in conjunction with computer vision and artificial intelligence techniques can be used to automate this process. This paper presents an approach to do segmentation of bees' wing images and feature extraction. Our approach was evaluated using the modified Hausdorff distance and F measure. The results were, at least, 24% more precise than the related approaches and the proposed approach was able to deal with noisy images.

Corrigendum to “A modified Hausdorff distance between fuzzy sets”

2002 ◽  
Vol 148 (1-4) ◽  
pp. 233-234 ◽  
Author(s):  
Kiran R. Bhutani ◽  
B.B. Chaudhuri ◽  
Azriel Rosenfeld
Keyword(s):  
Fuzzy Sets ◽  
Hausdorff Distance ◽  
Modified Hausdorff Distance

Hausdorff Distance for Face Recognition

2015 ◽  
pp. 39-46
Keyword(s):  
Face Recognition ◽  
Hausdorff Distance ◽  
Similarity Measures ◽  
Face Verification ◽  
3D Data ◽  
Modified Hausdorff Distance

When two sets are differently sized, the Hausdorff distance can be computed between them, even if the cardinality of one set is infinite. Different versions of this distance have been proposed and employed for face verification, among which the modified Hausdorff distance is the most famous. The important point to be noted is that, among the most commonly used similarity measures, the Hausdorff distance is the only one that has been widely applied to 3D data.

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