Computer vision at ECIL
Computer vision · Internship completed
Computer vision work for circuit-board inspection and print quality assurance.
- Role
- AI & ML Research Intern
- Period
- 2025
- Tools & focus
- Python · OpenCV · NumPy · Infrared imaging
The problem
PCB inspection involved finding micro-cracks and solder anomalies in infrared images. Print quality work involved reconstructing grayscale images affected by camera distortion and uneven lighting.
The approach
- Used Python and OpenCV for image enhancement and edge matching in PCB defect inspection.
- Automated image preprocessing and collaborated with hardware and software teams on the inspection pipeline.
- Used NumPy linear algebra to build spatial correction matrices for camera-captured print images.
The outcome
Developed PCB inspection and print-image reconstruction workflows during the internship, applying image enhancement, preprocessing, and matrix-based correction to industrial quality checks.