Challenge: Irregular hand-drawing styles, varying lighting conditions, and image resolution differences make pattern recognition difficult.
Solution: Image enhancement using Pillow and OpenCV achieves 85% accuracy across all image quality levels, ensuring robust performance regardless of input conditions.
Challenge: System may experience slowdowns during peak usage, potentially increasing cloud infrastructure costs.
Solution: Implementation of auto-scaling cloud infrastructure with Redis caching effectively handles 10× peak traffic while reducing operational costs by 60%.
Challenge: Dataset scarcity and unorganized collections may negatively impact solution outcomes.
Solution: Comprehensive collection of 1000+ patterns from diverse sources including museums, academic publications, expert networks, and university collaborations.