LASMU Computer Vision Project

Here are a few use cases for this project:

1. Digital Art Analysis: LASMU can be used by art enthusiasts, digital artists, and art curators to recognize various line stroke techniques, quality, or styles used in digital artwork, enhancing their ability to identify and appreciate distinct artistic approaches.

2. Handwriting Recognition and Analysis: LASMU can be employed in educational and psychological contexts to study handwriting features, such as line appearance and variations, potentially identifying handwriting traits or drawing patterns related to cognitive or developmental processes.

3. Document Digitization: Implementing LASMU can aid in the digitization and transcription of historical manuscripts, where differentiating line types such as text, annotations, and illustrations is essential for accurate digitization and preservation.

4. Automatic Line Type Mapping for Geographic Information System (GIS): LASMU can be used for analyzing cartographic maps, detecting unique line types and their corresponding meanings, which can then be utilized in updating and enriching GIS applications.

5. Manufacturing Quality Control: LASMU can be employed in manufacturing processes to monitor line drawings and schematics to ensure accuracy in design and fabrication. The system can quickly identify deviations from the original line pattern, improving overall production quality control.