基于色调分形维数的柑橘糖度和有效酸度检测  

Sugar Content and the Valid Acidity Test of the Citrus Based on the Fractal Dimensions of Hue

作　　者：曹乐平[1] 温芝元[2] 沈陆明[2] 

机构地区：[1]湖南生物机电职业技术学院教务处,长沙410127 [2]湖南农业大学理学院,长沙410128

出　　处：《农业机械学报》2010年第3期143-148,共6页Transactions of the Chinese Society for Agricultural Machinery

基　　金：湖南省自然科学基金资助项目(2007JJ6129);湖南省农业厅资助项目(2007004A);湖南省教育厅资助项目(2006D059)

摘　　要：研究了宫川温州蜜柑糖度及有效酸度的机器视觉检测技术及影响检测精度的因素。对机器视觉系统采集的柑橘图像进行图像裁切、亮度法去图像背景和RGB空间至HSI空间的转换,将柑橘色调范围分割为0°~20°、20°~40°、40°~60°、60°~80°、80°~100°和100°~120°共6个区域,提取各区域色调分形维数,以此作为BP神经网络输入,无损检测宫川温州蜜柑糖度及有效酸度。167个测试样本的检测结果表明：在±1.5°B rix精度范围内糖度正确识别率为66.6175%,在±0.5精度范围内有效酸度正确识别率为73.927 5%。宫川温州蜜柑糖度及有效酸度与果皮色调分形维数之间具有相关性,可用机器视觉检测其糖度及有效酸度。Non-destructive detection methods of sugar content and valid acidity of Gongchuan Wenzhou citrus fruits were investigated based on computer vision.Factors which influenced the accuracy of detection were studied.Citrus fruit images from computer vision system were cut,the background was removed and conversion from RGB to HSI space was made.These images were segmented according to hue value ranges which are 0°～20°,20°～40°,40°～60°,60°～80°,80°～100° and 100°～120° hue.Fractal dimensions of each segment were calculated as inputs of BP neural network which modeled sugar content and valid acidity of citrus fruits.Results of 167 test samples showed the correctness for accuracy ±1.5°Brix of sugar content is 66.617 5%,for valid acidity,the correctness for accuracy ±0.5 is 73.927 5%.From these results it concluded that sugar content and valid acidity of Gongchuan Wenzhou citrus fruits has significant correlation with fractal dimension of hue value of fruit pericarp.Computer vision can be utilized to non-destructively detect these two parameters.

关 键 词：柑橘 糖度 有效酸度 机器视觉 无损检测 色调 分形维数 

分 类 号：TS391.42[轻工技术与工程]