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Background segmentation and parameter detection of Jatropha seeds images |
WANG Huanchang, YANG Qiliang*, YANG Ying |
College of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650500, China |
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Abstract In order to solve the problems of low efficiency, strong subjectivity, high error rates and poor real time that when selecting the quality of Jatropha seeds by experience, the images of Jatropha seeds were analyzed by digital image processing technology in this paper. Aiming at the characteristics of Jatropha seeds images, the R,G,B color components by arithmetic were firsty fused, then the arithmetic results were processed for noise cancellation by morphological opening operation, the adaptive threshold selection method was used for these images which were converted into binary images according to the method of OTSU and the edge extraction of images was realized by way of LOG operator. The portion of Jatropha seeds morphology parameters with the procedure of image processing finally was also calculated and got. Compared with the artificial segmentation method, the experimenal results show that although the background segmentation of Jatropha seeds images produces certain errors because the Jatropha seeds which are irradiated by light generate unequal shaded area in various display modes, overall average error of segmentation is less than 0.63%, the maximum error is 1.07% and the mean square error σ is not over 0.006 4 in 90 images of Jatropha seeds. Above all, this algorithm can achieve the accurate and reliable background segmentation and parameter detection of Jatropha seeds images.
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Received: 19 March 2018
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