In the field of Cultural Heritage, different kinds of investigations are usually conducted in order to check the state of conservation of buildings and artifacts and plan restoration interventions. Quantification of the extension of degraded areas is usually performed by manually detecting decay areas, using image analysis as an indispensable tool of investigation. Nevertheless this procedure is cumbersome and time consuming; in addition, it is subjective and requires expertise. The purpose of this contribution is to show the results of investigations held in order to provide a methodology for restorers and Institutions called to preserve Cultural Heritage through restoration interventions planning, for the automatic detection of deteriorated areas within architectures and artifacts using colour images as a field of examination. Within our investigations, we selected images representing recurrent decays, as, for example, detachments, cracks and chromatic alterations and run them both to manual and to automatic recognition and selection tests, in order to subsequently compare the results obtained using the two approaches and evaluate the reliability of the automatic one. Results comparison included computational and user time, quantification of the decay area error between manual and automatically detected zones. Comparison between the automatic and the manual procedure showed that the automatic detection is faster and reliable in all our selected case studies. In addition to these aspects, as remote sensing technologies nowadays allow the creation of reality-based models of artifacts, the possibility to automatically extract and manage information derived from 2D images in a 3D environment can enrich documentation about their state of preservation. In this context, our methodology showed evident improvements in the segmentation of reality-based models derived from remote sensing, with important consequences in the evaluation of the entity and extension of decay areas on 3D geometry.
Corsi C., Manferdini A.M., Baroncini V. (2011). APPLICATION OF AUTOMATIC IMAGE SEGMENTATION TECHNIQUES TO REMOTE SENSING SURVEYS OF CULTURAL HERITAGE. ROMA : Valmar.
APPLICATION OF AUTOMATIC IMAGE SEGMENTATION TECHNIQUES TO REMOTE SENSING SURVEYS OF CULTURAL HERITAGE
CORSI, CRISTIANA;MANFERDINI, ANNA MARIA;BARONCINI, VALENTINA
2011
Abstract
In the field of Cultural Heritage, different kinds of investigations are usually conducted in order to check the state of conservation of buildings and artifacts and plan restoration interventions. Quantification of the extension of degraded areas is usually performed by manually detecting decay areas, using image analysis as an indispensable tool of investigation. Nevertheless this procedure is cumbersome and time consuming; in addition, it is subjective and requires expertise. The purpose of this contribution is to show the results of investigations held in order to provide a methodology for restorers and Institutions called to preserve Cultural Heritage through restoration interventions planning, for the automatic detection of deteriorated areas within architectures and artifacts using colour images as a field of examination. Within our investigations, we selected images representing recurrent decays, as, for example, detachments, cracks and chromatic alterations and run them both to manual and to automatic recognition and selection tests, in order to subsequently compare the results obtained using the two approaches and evaluate the reliability of the automatic one. Results comparison included computational and user time, quantification of the decay area error between manual and automatically detected zones. Comparison between the automatic and the manual procedure showed that the automatic detection is faster and reliable in all our selected case studies. In addition to these aspects, as remote sensing technologies nowadays allow the creation of reality-based models of artifacts, the possibility to automatically extract and manage information derived from 2D images in a 3D environment can enrich documentation about their state of preservation. In this context, our methodology showed evident improvements in the segmentation of reality-based models derived from remote sensing, with important consequences in the evaluation of the entity and extension of decay areas on 3D geometry.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
