Hardware-based image processing for high-speed inspection of grains

• Published in: Computers and electronics in agriculture 2009-11, Vol.69 (1), p.12-18
• Main Author: Pearson, Tom
• Format: Article
• Language: English
• Subjects: accuracy; Agronomy. Soil science and plant productions; automatic detection; Biological and medical sciences; CMOS; color; Corn; equipment performance; field-programmable gate array; FPGA; Fundamental and applied biological sciences. Psychology; grain inspection; grains; image analysis; imaging hardware; Machine vision; Popcorn; product defects; product development; quality control; rapid methods; Smart camera; sorting; Wheat
• ISSN: 0168-1699; 1872-7107
• DOI: 10.1016/j.compag.2009.06.007

A high-speed, low-cost, image-based sorting device was developed to detect and separate grains having slight color differences or small defects. The device directly combines a complementary metal–oxide–semiconductor (CMOS) color image sensor with a field-programmable gate array (FPGA) which was programmed to execute image processing in real-time, without the need of an external computer. Spatial resolution of the imaging system is approximately 16 pixels/mm. The system includes three image sensor/FPGA combinations placed around the perimeter of a single-file stream of kernels, so that most of the surface of each kernel is be inspected. A vibratory feeder feeds kernels onto an inclined chute that kernels slide down in a single-file manner. Kernels are imaged immediately after dropping off the end of the chute and are diverted by activating an air valve. The system has a throughput rate of approximately 75 kernels/s per channel which is much higher than previously developed image inspection systems. This throughput rate corresponds to an inspection rate of approximately 8 kg/h of wheat and 40 kg/h of popcorn. The system was initially developed to separate white wheat from red wheat, and to remove popcorn having blue-eye damage, which is indicated by a small blue discoloration in the germ of a popcorn kernel. Testing of the system resulted in accuracies of 88% for red wheat and 91% for white wheat. For popcorn, the system achieved 74% accuracy when removing popcorn with blue-eye damage and 91% accuracy at recognizing good popcorn. The sorter should find uses for removing other defects found in grain, such as insect-damaged grain, scab-damaged wheat, and bunted wheat. Parts for the system cost less than $2000, suggesting that it may be economical to run several systems in parallel to keep up with processing plant rates.