%0 Journal Article %1 Pearson2009 %A Pearson, Tom %D 2009 %J Computers and Electronics in Agriculture %K computer-vision grain high-speed %P - %R DOI: 10.1016/j.compag.2009.06.007 %T Hardware-based image processing for high-speed inspection of grains %U http://www.sciencedirect.com/science/article/B6T5M-4WSWYCF-1/2/881d8b7a1470dbb4fc192c334c6cba58 %V In Press, Corrected Proof %X 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.

@article{Pearson2009, abstract = {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.}, added-at = {2009-08-03T13:53:11.000+0200}, author = {Pearson, Tom}, biburl = {https://www.bibsonomy.org/bibtex/2eba3fc044ae3a96cfe17bbc7fc1ae803/nicole_koenderink}, description = {ScienceDirect - Computers and Electronics in Agriculture : Hardware-based image processing for high-speed inspection of grains}, doi = {DOI: 10.1016/j.compag.2009.06.007}, interhash = {732c16ac14a24bdf1a8f2dbbe4a33b19}, intrahash = {eba3fc044ae3a96cfe17bbc7fc1ae803}, issn = {0168-1699}, journal = {Computers and Electronics in Agriculture}, keywords = {computer-vision grain high-speed}, pages = { - }, timestamp = {2009-08-03T13:53:11.000+0200}, title = {Hardware-based image processing for high-speed inspection of grains}, url = {http://www.sciencedirect.com/science/article/B6T5M-4WSWYCF-1/2/881d8b7a1470dbb4fc192c334c6cba58}, volume = {In Press, Corrected Proof}, year = 2009 }