In order to improve sorting precision of granular agricultural products

a k-nearest neighbor（ k-NN）method based on FPGA is proposed. The method contains two steps: the first step

image obtained by FPGA-based color linear array CCD imaging system is saved on PC

and the obtained image is feature extracted

and then using k-NN method extracted features are screened and obtain the optinal feature set. The second step

trained the optimal feature set is put on FPGA-ROM

FPGA real-time extract characteristics of image data obtained by linear CCD on ROM and optimal feature set make distance calculation

achieve k-NN sorting algorithms. Two kinds of granular agricultural products

peanuts and pistachios

are tested by this method

RGB color space as main feature

the results show that under reasonable choice in the number and characteristics of the K-value situations

sorting correct rate of peanuts and pistachios reach above 95 %.