Visual classification is simple for humans, but machines face significant challenges when identifying objects in images. Whether it’s detecting faulty products, categorizing facial expressions, or distinguishing produce, computer vision and deep learning provide powerful solutions.

Classic Computer Vision Approach

Traditional classification relies on features such as color, shape, and texture. For example, distinguishing a peach from a nectarine depends on surface texture, since color and shape are similar. Using tools like MVTec Halcon, this approach can correctly classify most objects under ideal conditions.

• Example: Using Halcon’s identifier, 69/70 fruit images were classified correctly (1.4% error rate).
  
• Challenge: When fruits were placed in plastic bags, texture detection became difficult, reducing accuracy to 60/70 images (14.8% error rate), which is insufficient for industrial standards.
  

Deep Learning Approach

Deep learning, based on artificial neural networks, learns patterns from data without explicitly specifying features. It mimics how humans recognize objects, allowing machines to classify items accurately even under challenging conditions.

• Example: Applying deep learning to fruits and vegetables in plastic bags achieved 100% accuracy (70/70 images).
  
• Benefits: Deep learning improves reliability, reduces error rates, and can be scaled for automated sorting and quality control in retail and production environments.
  

Business Impact

• Accurate classification in varying conditions (e.g., packaging, lighting),
  
• Automated inspection for fruits, vegetables, and other products,
  
• Reduced labor and errors in quality control processes,
  
• Scalable AI solutions for machine vision applications.
  

Conclusion

Whether in production lines, grocery stores, or packaging facilities, deep learning and computer vision outperform traditional methods, ensuring high-speed, accurate classification for fruits, vegetables, and other products.

Want to implement AI-powered classification for your production or retail operations?
Contact us at info@subpixel.hr to see how Subpixel’s deep learning and computer vision solutions can improve accuracy and efficiency.