Exploiting a Semi-Automatic Point Cloud Segmentation Method to Improve the Quality of Rock-Mass Characterization. The Cima Grappa Conservative Restoration Case Study

Mugnai, Francesco; Farina, Paolo; Tucci, Grazia

doi:10.3390/ijgi10050276

Cited by 6 publications

(3 citation statements)

References 47 publications

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“…e development of ink painting simulation is still in a relative stage of development compared with the development of computer simulation in western painting, and the rendering of ink painting in film and animation is still in a relative stage of development [9,10]. ere is still a huge gap in the rendering simulation of ink painting in the fields of film, television, and animation [11,12]. erefore, it is necessary to conduct research on ink painting rendering [13,14].…”

Section: Introductionmentioning

confidence: 99%

Morphological Structural Element Optimization for Automatic Line Characterization of Ink Drawings

2022

Security and Communication Networks

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As a traditional Chinese art, the tools of Chinese ink painting are mainly brushes, ink, and rice paper and ink stone. As an important form of ink painting, ink landscape painting consists of ink lines that first outline the overall trend of the mountain and then complete the basic process of painting with rich chapping techniques. The article proposes a process to draw water animation based on Chinese painting style; this method first perceives the position of water form in Chinese painting and enhances it by morphological structural elements used to automatically draw the line feature analysis of ink painting; next, the image rendering technique is used to render the water form, firstly using BF for noise removal processing and then gradienting by Canny edge detection operator to get the gradient amplitude. Next, morphological optimization is applied, and finally the image is visualized. In the process of morphological optimization, the optimal parameters of the structural elements are found through the threshold segmentation number, and the rendering algorithm for ink-based landscape painting is explored in depth, starting from the ink lines. The results reveal that the method is more accurate than typical marker-watershed algorithm segmentation, and that changing different structural elements and their parameters has a bigger impact on the ink painting drawing effect.

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Section: Introductionmentioning

confidence: 99%

Morphological Structural Element Optimization for Automatic Line Characterization of Ink Drawings

2022

Security and Communication Networks

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“…By processing point clouds, some of the rock-mass parameters (Barton et al, 1974;PRIEST, 1993) are block size, the number of sets, persistence, orientation (Figure 7), spacing/frequency (and derived RQD), and scale-dependent roughness can be determined. As reported in (Mugnai et al, 2021), the method allows to identifying principal plains on the point cloud by applying best fitting planes algorithm through a searching cube which contains a selection of a point cloud subset.…”

Section: D Kinematic Stability Analysis Of the Rock Massmentioning

confidence: 99%

Laser Scanning and Point Cloud Segmentation for Contactless Geo-Mechanical Surveying: Conservative Restoration in Hypogeum Environment

Mugnai

2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The work presents a survey campaign specifically designed to formulate an effective restoration project in a Cultural Heritage context, the Military Shrine in Cima Grappa (Italy). Several outputs have been generated by exploring the most advanced laser scanning survey technique and some specific point cloud analysis algorithms. A detailed geometrical 3D reconstruction of human-made and natural tunnels coating materials, a geo-mechanical survey of the rock mass, a map of rock collapses and cinematic analysis of instability processes.Integrating Laser Scanning technique with the Scan-line survey allowed to perform advanced analysis and rock-mass characterisation in a predominant subterranean developed area. Most of the tunnels and underground spaces displayed rock collapses and diffuse active instability processes that certainly could have drastically slowed down surveys and analysis. The adopted techniques allowed both to proceed in acquiring data end in delivering sound outputs rapidly.

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“…In (Gonizzi Barsanti et al, 2017), authors test several methodologies and algorithms available to segment a 3D point cloud or a mesh for cultural heritage structural analysis. While other work shows how to exploit a semi-automatic segmentation method to improve material characterization, only based on the point cloud (Mugnai et al, 2021). In this field, Machine Learning (ML) algorithms are increasingly being applied to automatic classification processes.…”

Section: Introductionmentioning

confidence: 99%

Point Cloud Segmentation in Heritage Preservation. Advanced Digital Process for Historical Houses

Nespeca,

Mariotti,

Petetta

et al. 2024

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This paper discusses the use of point cloud segmentation, both automatic and semi-automatic, in heritage conservation processes, with the aim of consciously integrating traditional and innovative methods. Thus, the research explores the potential of open-source software tools for semi-automatic point-cloud segmentation in enriching heritage knowledge and contributing to the inspection of its state of conservation. This ensures a 3D geometric view of reality and enables the identification of criticalities that may not be visible to the naked eye through colorimetric attributes. The study was conducted on Villa Leonardi, a historical house located in the city of Treia in the Marche Region (Italy) as a pilot test. The investigation focused on the east and south elevations of the building, which were suitable for two distinct trials: a semi-automatic procedure for analyzing the quality of mortar joints in an exposed masonry, and a semi-automatic procedure for mapping alterations and decay in a plastered masonry. To validate the results, manual and semi-automatic maps were compared using both qualitative and quantitative assessments. Qualitative assessment involved overlay and visual analysis, while quantitative assessment involved transforming the segmented point cloud into a mesh and calculating the resulting surface area. The critical interpretation of the two trials revealed both advantages and disadvantages; overall, experimentation highlighted the added value that advanced digital process can bring to the issue of heritage preservation.

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Exploiting a Semi-Automatic Point Cloud Segmentation Method to Improve the Quality of Rock-Mass Characterization. The Cima Grappa Conservative Restoration Case Study

Cited by 6 publications

References 47 publications

Morphological Structural Element Optimization for Automatic Line Characterization of Ink Drawings

Morphological Structural Element Optimization for Automatic Line Characterization of Ink Drawings

Laser Scanning and Point Cloud Segmentation for Contactless Geo-Mechanical Surveying: Conservative Restoration in Hypogeum Environment

Point Cloud Segmentation in Heritage Preservation. Advanced Digital Process for Historical Houses

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