Implementation of the smartphone camera in the measures of narrow street facades
This paper aims to perform metric measurements of narrow street façades using single image captured by smartphone’s camera. Since tight area accompanied by narrow street limits object to camera distance, object lines perpendicular to façade do not appear in image and consequently their vanishing po...
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| Format: | Article |
| Language: | English |
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Vilnius Gediminas Technical University
2023-03-01
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| Series: | Geodesy and Cartography |
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| Online Access: | https://jbem.vgtu.lt/index.php/GAC/article/view/16529 |
| _version_ | 1797871813663916032 |
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| author | Mohammed Aldelgawy |
| author_facet | Mohammed Aldelgawy |
| author_sort | Mohammed Aldelgawy |
| collection | DOAJ |
| description |
This paper aims to perform metric measurements of narrow street façades using single image captured by smartphone’s camera. Since tight area accompanied by narrow street limits object to camera distance, object lines perpendicular to façade do not appear in image and consequently their vanishing point (VP) is hard to detect. Accordingly, semi-automated MATLAB® application was designed depending only on two orthogonal VPs. Novelty of work comes from using smartphone as a cost and time efficient tool for measurements, depending only on two VPs, and applying image line refinement approach exploiting detected VPs. Three single images were captured by three different smartphones. Then, undistorted single images were formed after calibrating cameras. Image lines for horizontal and vertical object lines were extracted semi-automatically. Two VPs were detected applying two models: Model-I solves for vanishing points’ Cartesian coordinates, whereas Model-II solves for angle coordinate peaks of histogram. Image line refinement approach was applied before applying cross-ratio using one horizontal and one vertical reference lines to calculate object lengths of 46 check lines (horizontal and vertical). Proposed models provided reliable and comparable results. Applying line refinement approach improved solution with best overall accuracy of 0.010 m and 0.011 m for Model-I and Model-II, respectively.
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| first_indexed | 2024-04-10T00:50:00Z |
| format | Article |
| id | doaj.art-ad6e2c6719084b31818ec711249c81ea |
| institution | Directory Open Access Journal |
| issn | 2029-6991 2029-7009 |
| language | English |
| last_indexed | 2024-04-10T00:50:00Z |
| publishDate | 2023-03-01 |
| publisher | Vilnius Gediminas Technical University |
| record_format | Article |
| series | Geodesy and Cartography |
| spelling | doaj.art-ad6e2c6719084b31818ec711249c81ea2023-03-13T16:16:40ZengVilnius Gediminas Technical UniversityGeodesy and Cartography2029-69912029-70092023-03-0149110.3846/gac.2023.16529Implementation of the smartphone camera in the measures of narrow street facadesMohammed Aldelgawy0Civil Engineering Department, Faculty of Engineering, Fayoum University, Fayoum, Egypt This paper aims to perform metric measurements of narrow street façades using single image captured by smartphone’s camera. Since tight area accompanied by narrow street limits object to camera distance, object lines perpendicular to façade do not appear in image and consequently their vanishing point (VP) is hard to detect. Accordingly, semi-automated MATLAB® application was designed depending only on two orthogonal VPs. Novelty of work comes from using smartphone as a cost and time efficient tool for measurements, depending only on two VPs, and applying image line refinement approach exploiting detected VPs. Three single images were captured by three different smartphones. Then, undistorted single images were formed after calibrating cameras. Image lines for horizontal and vertical object lines were extracted semi-automatically. Two VPs were detected applying two models: Model-I solves for vanishing points’ Cartesian coordinates, whereas Model-II solves for angle coordinate peaks of histogram. Image line refinement approach was applied before applying cross-ratio using one horizontal and one vertical reference lines to calculate object lengths of 46 check lines (horizontal and vertical). Proposed models provided reliable and comparable results. Applying line refinement approach improved solution with best overall accuracy of 0.010 m and 0.011 m for Model-I and Model-II, respectively. https://jbem.vgtu.lt/index.php/GAC/article/view/16529single imagemetric measurementsfaçade observationvanishing pointcross-ratiosmartphone’s camera |
| spellingShingle | Mohammed Aldelgawy Implementation of the smartphone camera in the measures of narrow street facades Geodesy and Cartography single image metric measurements façade observation vanishing point cross-ratio smartphone’s camera |
| title | Implementation of the smartphone camera in the measures of narrow street facades |
| title_full | Implementation of the smartphone camera in the measures of narrow street facades |
| title_fullStr | Implementation of the smartphone camera in the measures of narrow street facades |
| title_full_unstemmed | Implementation of the smartphone camera in the measures of narrow street facades |
| title_short | Implementation of the smartphone camera in the measures of narrow street facades |
| title_sort | implementation of the smartphone camera in the measures of narrow street facades |
| topic | single image metric measurements façade observation vanishing point cross-ratio smartphone’s camera |
| url | https://jbem.vgtu.lt/index.php/GAC/article/view/16529 |
| work_keys_str_mv | AT mohammedaldelgawy implementationofthesmartphonecamerainthemeasuresofnarrowstreetfacades |