基于显著性特征的食用菌中杂质检测

计算机科学 ›› 2015, Vol. 42 ›› Issue (Z11): 203-205.

基于显著性特征的食用菌中杂质检测

徐振驰,纪磊,刘晓荣,周晓佳

浙江工商大学信息与电子工程学院杭州310018,浙江工商大学信息与电子工程学院杭州310018,浙江工商大学信息与电子工程学院杭州310018,浙江工商大学金融学院杭州310018

出版日期:2018-11-14 发布日期:2018-11-14

Recognition of Impurities Based on their Distinguishing Feature in Mushrooms

XU Zhen-chi, JI Lei, LIU Xiao-rong and ZHOU Xiao-jia

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 为了使用机器视觉实现对食用菌中发丝等杂质的自动检测,提出基于显著性特征的菌菇中杂质图像分割算法,该算法结合了Hessian灰度特征和Lab空间色彩特征,通过图像归一化、求Hessian矩阵、反向投影、取阈值分割出杂质图像。实验结果表明,该算法在光照不均匀条件下的识别率仍达到99.6%,可以用于工业化生产。

关键词: 机器视觉,黑塞矩阵,反向投影,杂质检测

Abstract: In order to achieve automatic recognition of hair impurities in edible mushrooms industry,a fingerprint image segmentation method based on impurity’s distinguishing feature in mushrooms was proposed in this paper.This algorithm segments the impurity’s image through the way of the image normalization,taking the Hessian matrix back projection,taking the threshold and combining the Hessian grayscale characteristics and Lab color space.These experimental results show that it also performs well and recongnition rate is up to 99.6％ in the case of nonuniform lighting conditions,which can be used in industrial production.

Key words: Machine vision,Hessian matrix,Back projection,Impurity recognition

徐振驰,纪磊,刘晓荣,周晓佳. 基于显著性特征的食用菌中杂质检测[J]. 计算机科学, 2015, 42(Z11): 203-205. https://doi.org/

XU Zhen-chi, JI Lei, LIU Xiao-rong and ZHOU Xiao-jia. Recognition of Impurities Based on their Distinguishing Feature in Mushrooms[J]. Computer Science, 2015, 42(Z11): 203-205. https://doi.org/

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