An Automatic Extraction Method for Road Maps using LiDAR-based 3D Point Maps

2021 ◽  
Vol 27 (5) ◽  
pp. 234-240
Author(s):  
Kyujin Choi ◽  
Kanghee Kim
Keyword(s):  
Extraction Method ◽  
Automatic Extraction ◽  
Road Maps

scholarly journals Extraction of Visible Boundaries for Cadastral Mapping Based on UAV Imagery

2019 ◽  
Vol 11 (13) ◽  
pp. 1510 ◽  
Author(s):  
Bujar Fetai ◽  
Krištof Oštir ◽  
Mojca Kosmatin Fras ◽  
Anka Lisec
Keyword(s):  
Optical Sensors ◽  
Extraction Method ◽  
Accuracy Assessment ◽  
Developed Countries ◽  
Automatic Extraction ◽  
Post Processing ◽  
Ground Sample ◽  
Cadastral Maps ◽  
Aerial Vehicle ◽  
Mapping Techniques

In order to transcend the challenge of accelerating the establishment of cadastres and to efficiently maintain them once established, innovative, and automated cadastral mapping techniques are needed. The focus of the research is on the use of high-resolution optical sensors on unmanned aerial vehicle (UAV) platforms. More specifically, this study investigates the potential of UAV-based cadastral mapping, where the ENVI feature extraction (FX) module has been used for data processing. The paper describes the workflow, which encompasses image pre-processing, automatic extraction of visible boundaries on the UAV imagery, and data post-processing. It shows that this approach should be applied when the UAV orthoimage is resampled to a larger ground sample distance (GSD). In addition, the findings show that it is important to filter the extracted boundary maps to improve the results. The results of the accuracy assessment showed that almost 80% of the extracted visible boundaries were correct. Based on the automatic extraction method, the proposed workflow has the potential to accelerate and facilitate the creation of cadastral maps, especially for developing countries. In developed countries, the extracted visible boundaries might be used for the revision of existing cadastral maps. However, in both cases, the extracted visible boundaries must be validated by landowners and other beneficiaries.

Research of Text Topic Automatic Extraction Method Based on Rough Set Theory

2011 ◽  
Vol 268-270 ◽  
pp. 1127-1131 ◽  
Author(s):  
Zhan Feng Sun ◽  
Kong Jun Bao
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Extraction Method ◽  
Rough Set Theory ◽  
Complete Information ◽  
Text Clustering ◽  
Automatic Extraction ◽  
Similarity Matrix ◽  
Topic Extraction ◽  
Automatic Abstracting

On the base of researching currently popular text topic extraction technologies, a new text topic automatic abstracting method is proposed based on rough set theory and rough similarity. Firstly it separated a text into words and sentences to complete information segmentation, and then constructed a similarity matrix by computing the rough similarity between different words to realize the text clustering, finally extracted representative sentences from each class to generate the text topic. The experiment shows that the method is feasible and effective.

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