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Author: Yi Xun Junxiong Zhang Wei Li Weiguo Cai
Publisher: Taylor & Francis Ltd
ISSN: 1002-0071
Source: Progress in Natural Science, Vol.17, Iss.2, 2007-02, pp. : 217-221
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
An approach to inspecting massive numbers of moving seeds was studied based on the technqiues to dynamic inspection and machine vision. A progressive scanning CCD camera with external trigger function was used for real-time capture of dynamic images of seeds. The methods based on R channel of RGB (Red, Gree and Blue) and region-dependent segmentation were adopted to reduce the data size of image processing and improve the efficiency of seeds inspection. All the seeds were sorted into foud grades according to their morphological characteristics, such as surface area, perimeter, major axis, circularity and eccentricity. The detection experiments indicated that the eligible ratio of the classifications was about 81.90% by this real-time inspection system.
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