Recognition of materials and damage on historical buildings using digital image classification
Nowadays, techniques in digital image processing make it possible to detect damage, such as moisture or biological changes, on the surfaces of historical buildings. Digital classification techniques can be used to identify damages in construction materials in a non-destructive way. In this study, we...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Academy of Science of South Africa
2015-01-01
|
| Series: | South African Journal of Science |
| Subjects: | |
| Online Access: | https://www.sajs.co.za/article/view/3515 |
| _version_ | 1818498342029623296 |
|---|---|
| author | José E. Meroño Alberto J. Perea María J. Aguilera Ana M. Laguna |
| author_facet | José E. Meroño Alberto J. Perea María J. Aguilera Ana M. Laguna |
| author_sort | José E. Meroño |
| collection | DOAJ |
| description | Nowadays, techniques in digital image processing make it possible to detect damage, such as moisture or biological changes, on the surfaces of historical buildings. Digital classification techniques can be used to identify damages in construction materials in a non-destructive way. In this study, we evaluate the application of the object-oriented classification technique using photographs taken with a Fujifilm IS-Pro digital single lens reflex camera and the integration of the classified images in a three-dimensional model obtained through terrestrial laser scanning data in order to detect and locate damage affecting biocalcarenite stone employed in the construction of the Santa Marina Church (Córdoba, Spain). The Fujifilm IS-Pro camera captures spectral information in an extra-visible range, generating a wide spectral image with wavelengths ranging from ultraviolet to infrared. Techniques of object-oriented classification were applied, taking into account the shapes, textures, background information and spectral information in the image. This type of classification requires prior segmentation, defined as the search for homogeneous regions in an image. The second step is the classification process of these regions based on examples. The output data were classified according to the kind of damage that affects the biocalcarenite stone, reaching an overall classification accuracy of 92% and an excellent kappa statistic (85.7%). We have shown that multispectral classification with visible and near-infrared bands increased the degree of recognition among different damages. Post-analysis of these data integrated in a three-dimensional model allows us to obtain thematic maps with the size and position of the damage. |
| first_indexed | 2024-12-10T18:57:32Z |
| format | Article |
| id | doaj.art-7442a0fd6afa4aa1ac261a3de8647cbe |
| institution | Directory Open Access Journal |
| issn | 1996-7489 |
| language | English |
| last_indexed | 2024-12-10T18:57:32Z |
| publishDate | 2015-01-01 |
| publisher | Academy of Science of South Africa |
| record_format | Article |
| series | South African Journal of Science |
| spelling | doaj.art-7442a0fd6afa4aa1ac261a3de8647cbe2022-12-22T01:37:07ZengAcademy of Science of South AfricaSouth African Journal of Science1996-74892015-01-011111/21910.17159/sajs.2015/201400013515Recognition of materials and damage on historical buildings using digital image classificationJosé E. Meroño0Alberto J. Perea1María J. Aguilera2Ana M. Laguna3Department of Graphics Engineering and Geomatics, University of Cordoba, Córdoba, SpainDepartment of Applied Physics, University of Cordoba, Córdoba, SpainDepartment of Applied Physics, University of Cordoba, Córdoba, SpainDepartment of Applied Physics, University of Cordoba, Córdoba, SpainNowadays, techniques in digital image processing make it possible to detect damage, such as moisture or biological changes, on the surfaces of historical buildings. Digital classification techniques can be used to identify damages in construction materials in a non-destructive way. In this study, we evaluate the application of the object-oriented classification technique using photographs taken with a Fujifilm IS-Pro digital single lens reflex camera and the integration of the classified images in a three-dimensional model obtained through terrestrial laser scanning data in order to detect and locate damage affecting biocalcarenite stone employed in the construction of the Santa Marina Church (Córdoba, Spain). The Fujifilm IS-Pro camera captures spectral information in an extra-visible range, generating a wide spectral image with wavelengths ranging from ultraviolet to infrared. Techniques of object-oriented classification were applied, taking into account the shapes, textures, background information and spectral information in the image. This type of classification requires prior segmentation, defined as the search for homogeneous regions in an image. The second step is the classification process of these regions based on examples. The output data were classified according to the kind of damage that affects the biocalcarenite stone, reaching an overall classification accuracy of 92% and an excellent kappa statistic (85.7%). We have shown that multispectral classification with visible and near-infrared bands increased the degree of recognition among different damages. Post-analysis of these data integrated in a three-dimensional model allows us to obtain thematic maps with the size and position of the damage.https://www.sajs.co.za/article/view/3515digital classificationmultispectral imagesterrestrial laser scannerdiagnostic of cultural heritagebiocalcarenite stone |
| spellingShingle | José E. Meroño Alberto J. Perea María J. Aguilera Ana M. Laguna Recognition of materials and damage on historical buildings using digital image classification South African Journal of Science digital classification multispectral images terrestrial laser scanner diagnostic of cultural heritage biocalcarenite stone |
| title | Recognition of materials and damage on historical buildings using digital image classification |
| title_full | Recognition of materials and damage on historical buildings using digital image classification |
| title_fullStr | Recognition of materials and damage on historical buildings using digital image classification |
| title_full_unstemmed | Recognition of materials and damage on historical buildings using digital image classification |
| title_short | Recognition of materials and damage on historical buildings using digital image classification |
| title_sort | recognition of materials and damage on historical buildings using digital image classification |
| topic | digital classification multispectral images terrestrial laser scanner diagnostic of cultural heritage biocalcarenite stone |
| url | https://www.sajs.co.za/article/view/3515 |
| work_keys_str_mv | AT joseemerono recognitionofmaterialsanddamageonhistoricalbuildingsusingdigitalimageclassification AT albertojperea recognitionofmaterialsanddamageonhistoricalbuildingsusingdigitalimageclassification AT mariajaguilera recognitionofmaterialsanddamageonhistoricalbuildingsusingdigitalimageclassification AT anamlaguna recognitionofmaterialsanddamageonhistoricalbuildingsusingdigitalimageclassification |