Open Area Interference

Project Objective:

To develop a machine learning image recognition model to analyze interference areas across two overlapping perforated metal sheets rotating at various angles. This model was used to select acceptable combinations of perforation patterns for stable open area and flow performance.

Skills Demonstrated:

• AI image processing

• Data Extraction

• Real-time analysis techniques

Optimized Video Capture for Open Area Calculation:

This project is a compelling showcase of practical computer vision in action by automating the analysis of video footage to quantify changes in open area using light intensity. The script efficiently processes video frames to extract meaningful metrics like average brightness and maps them over time and angle—tools often used in robotics, automation, and quality inspection systems. Its integration of OpenCV and NumPy reflects both programming proficiency and the ability to apply AI-adjacent tools to solve real-world sensing problems. This project highlights not only technical skills but also creativity in using vision systems for environmental and spatial analysis.