Quantity Detection of Kernels in an Ear Corn Based on Machine Vision

Chang Qing Liu; Bing Qi Chen; Yang Liu; Tao Zha

doi:10.4028/www.scientific.net/AMM.246-247.279

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 246-247Quantity Detection of Kernels in an Ear Corn Based...

Quantity Detection of Kernels in an Ear Corn Based on Machine Vision

Abstract:

A high efficient method is provided to count the number of kernels in an ear corn. PC camera captured a sequence of images around an ear corn using a simple device. The Otsu's algorithm was applied for background segmentation. An object processing area was obtained after contour extraction. The x-direction cumulative histogram was used to extract every row of the ear corn. The y-direction cumulative histogram was used to detect the number of corn kernels in a row. The number of rows was got by matching the edge of the current ear row with the first one. The time of detecting kernels for an ear corn was below 2 minutes and the average accuracy was about 95% in experiment. It shows that this method can detect the quantity of kernels directly in an ear corn quickly and effectively using a low-cost device.

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Periodical:

Applied Mechanics and Materials (Volumes 246-247)

Pages:

279-285

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.246-247.279

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Online since:

December 2012

Authors:

Chang Qing Liu, Bing Qi Chen, Yang Liu, Tao Zha

Keywords:

Counting Kernels, Ear Corn, Image Processing, Machine Vision, PC Camera

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