Sunflower Seed Sorting Challenge: How to Solve the Problem of Wormholes and White Spots? The AI Color Sorter Provides the Answer

In sunflower seed processing, wormholes and white spots are two of the most common types of hidden defects.

Wormholes: Tiny holes with a color similar to that of normal kernels.

White spots: Localized whitening on the seed surface, light in color and irregular in shape.

These two defects directly lower the quality of the final product. The new AI Deep Learning Color Sorter, specially customized for sunflower seeds, accurately identifies wormholes and white spots.

HAWIT’s Triple Engine – Pinpoints Every Defective Seed

1. Optical Sensing
Equipped with high-definition lenses, every sunflower seed is captured at high speed, producing clear images with fine detail. Tiny wormholes and light-colored white spots are fully revealed under the lens, providing high-quality image data for subsequent algorithm recognition.

2. Algorithmic Decision-Making
Built on a self-training model based on deep learning, no manual parameter adjustment is required. It integrates multi-dimensional features such as color, shape, and texture, greatly reducing the false positive rate and becoming more accurate with use.

3. Execution Coordination
After AI completes recognition and judgment within milliseconds, instructions are instantly transmitted to high-speed solenoid valves for precise rejection. This coordination mechanism breaks through the speed bottleneck of traditional color sorters, maintaining high throughput while improving rejection accuracy.

The new AI Deep Learning Color Sorter – with high-definition vision as its core, deep learning algorithms as its brain, and high-speed coordinated execution as its hand – specializes in overcoming hidden defects like wormholes and white spots, making sunflower seed sorting clearer, more accurate, and more reliable.