Segmentation and Analysis of a Sketched Truss Frame Using Morphological Image Processing Techniques (2009.13144v1)

Abstract: Development of computational tools to analyze and assess the building capacities has had a major impact in civil engineering. The interaction with the structural software packages is becoming easier and the modeling tools are becoming smarter by automating the users role during their interaction with the software. One of the difficulties and the most time consuming steps involved in the structural modeling is defining the geometry of the structure to provide the analysis. This paper is dedicated to the development of a methodology to automate analysis of a hand sketched or computer generated truss frame drawn on a piece of paper. First, we focus on the segmentation methodologies for hand sketched truss components using the morphological image processing techniques, and then we provide a real time analysis of the truss. We visualize and augment the results on the input image to facilitate the public understanding of the truss geometry and internal forces. MATLAB is used as the programming language for the image processing purposes, and the truss is analyzed using Sap2000 API to integrate with MATLAB to provide a convenient structural analysis. This paper highlights the potential of the automation of the structural analysis using image processing to quickly assess the efficiency of structural systems. Further development of this framework is likely to revolutionize the way that structures are modeled and analyzed.

• The paper introduces an automated process that segments and analyzes truss components using morphological image processing combined with Sap2000.
• The methodology accurately isolates joints, members, arrows, and supports by applying erosion techniques and straight-line assumptions.
• Integration of OCR for text recognition and API-driven analysis streamlines structural evaluation and overlays computed forces on original images.

Automated Structural Analysis of Sketched Truss Frameworks Using Image Processing

This paper presents a novel methodology aimed at automating the analysis of sketched or computer-generated truss frames using image processing techniques. The process integrates image processing in MATLAB with structural analysis via the Sap2000 API, showcasing a concerted effort to streamline the traditionally labor-intensive task of geometric definition in structural modeling. The automation of these processes not only expedites the structural assessment but also seeks to improve the accuracy and accessibility of such evaluations.

The paper focuses on using morphological image processing to segment and recognize components of truss diagrams. It primarily involves six essential steps: converting the truss image to a binary gray-scale representation, segmenting truss components such as joints, members, arrows, and supports, recognizing character strings via Optical Character Recognition (OCR), validating the data, performing the structural analysis using the Sap2000 API, and finally, overlaying the results on the original input image.

Key Methodological Insights

1. Image Processing and Segmentation: The paper articulates a meticulous approach to segmenting truss components by leveraging MATLAB's image processing toolbox. The process begins with generating a gray-scale binary image and progresses through distinct segmentation strategies for various truss components. The erosion technique is utilized to ascertain joint locations, while straight-line assumptions in truss members streamline the validation of their presence between joint elements. The identification of arrows and supports is refined using morphological properties, ensuring accurate representation and distinction between different structural elements.
2. Optical Character Recognition (OCR): A significant challenge addressed in this research is the recognition of arbitrarily oriented text strings. This is handled by calculating slopes for individual text strings to align them horizontally for effective OCR processing. The methodology specifically accounts for issues like upside-down text recognition by employing criteria based on average character comparison scores.
3. Integration with Sap2000 for Analysis: Automated interaction between MATLAB and Sap2000 is employed, allowing the derived structural information to be sent for analysis via the Sap2000 API. This step includes translating geometry and loading parameters into the API and receiving analysis outcomes that are subsequently overlaid onto the input image, enabling users to visually interpret structural forces such as axial loads with ease.

Implications and Future Directions

The implications of this research are manifold. Practically, the methodology could significantly reduce the manual effort involved in defining structural geometries for truss analysis, thereby accelerating project timelines and enhancing cost efficiency. From a theoretical standpoint, the integration of image processing with structural analysis through APIs can potentially transform conventional modeling approaches, encouraging the development of intelligent and adaptive engineering applications.

Future research directions suggested in the paper include extending the methodology to analyze fixed 2D rigid frames, visualizing deformed structures, and examining shear and moment forces in members. Additionally, further advancements could culminate in quickly generating Building Information Models (BIM) from architectural drawings, thus paving the way for more comprehensive automation in civil engineering structural analysis, including assessing seismic performance.

In conclusion, this paper illustrates a methodical approach to merging image processing with structural analysis, showcasing a potential paradigm shift in civil engineering by automating truss analysis and facilitating a deeper understanding of structural behavior through augmented visual outputs.