Proceedings PaperSeed maize quality inspection with machine vision
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A potential on-line automatic inspection system for grading seed maizes using machine vision was proposed. A number of samples of the maize images can be acquired as the maize cobs passing through the inspection system. The samples represent the quality of inspected maizes at different layers of unloading maizes from a truck. Machine vision algorithms were developed to measure the amount of residues mixing up with maize cobs and the loss of kernels on cobs. The methodology will be presented and discussed. Two parameters, residue mixture ratio and kernel loss ratio are introduced as indicators for quantitative measurement of the amount of residues mixed with cobs and kernel lost on the cobs.