Summary of Advanced Knowledge Extraction Of Physical Design Drawings, Translation and Conversion to Cad Formats Using Deep Learning, by Jesher Joshua M et al.
Advanced Knowledge Extraction of Physical Design Drawings, Translation and conversion to CAD formats using Deep Learning
by Jesher Joshua M, Ragav V, Syed Ibrahim S P
First submitted to arxiv on: 17 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed methodology uses deep learning methods to convert physical machine drawings to their digital forms, such as Computer-Aided Design (CAD) files. The approach employs object detection models like Yolov7 and Faster R-CNN to detect drawing objects, followed by edge detection algorithms and curve detection techniques to extract and refine lines from the drawing region. Ornaments within the drawings are also extracted using these methods. To ensure comprehensive conversion, an Optical Character Recognition (OCR) tool is integrated to identify and extract text elements from the drawings. The extracted data is consolidated and stored in a structured comma-separated values (.csv) file format. Evaluation metrics assess the accuracy and efficiency of the conversion process. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper proposes a new way to convert physical machine drawings into digital formats, like CAD files. It uses special computer programs that can recognize objects, lines, shapes, and text on the drawings. These programs are trained using deep learning methods and work together to extract all the important information from the drawings. The result is a digital file that contains all the original details, which can be easily shared or stored. This new method can help companies be more productive, collaborate better, and keep track of their valuable design information. |
Keywords
* Artificial intelligence * Cnn * Deep learning * Object detection
