You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
17 December 1993Seed maize quality inspection with machine vision
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.
The alert did not successfully save. Please try again later.
Jiancheng Jia, "Seed maize quality inspection with machine vision," Proc. SPIE 1989, Computer Vision for Industry, (17 December 1993); https://doi.org/10.1117/12.164872