Study on method of apple grading based on hidden Markov model

Authors

XIE Fengyun, School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang， Jiangxi 330013, China
ZHOU Jianmin, School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang， Jiangxi 330013, China
JIANG Weiwen, School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang， Jiangxi 330013, China
ZHANG Huihui, School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang， Jiangxi 330013, China
TANG Hongbing, School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang， Jiangxi 330013, China

Abstract

In order to adapt to the request of apple grading technology, a classification method for apple grading was proposed based on hidden Markov model (HMM). Three different colors and shapes of apples were studied. The hexagonal pyramid model (HSV) was extracted as the color features of the apple, and the Hu invariant moment was extracted as shape features of the apple. These features of the apple were coded by Lloyd algorithm, which was used as the inputting of HMM. According to the HMM pattern recognition method, the different colors and shapes of apples were identified and classified, and then the apple grading was completed. The tests showed that the apple grading results were correct by the proposed method.

Publication Date

7-28-2016

First Page

29

Last Page

31,111

DOI

10.13652/j.issn.1003-5788.2016.07.007

Recommended Citation

Fengyun, XIE; Jianmin, ZHOU; Weiwen, JIANG; Huihui, ZHANG; and Hongbing, TANG (2016) "Study on method of apple grading based on hidden Markov model," Food and Machinery: Vol. 32: Iss. 7, Article 7.
DOI: 10.13652/j.issn.1003-5788.2016.07.007
Available at: https://www.ifoodmm.cn/journal/vol32/iss7/7

References

[1] 饶秀勤, 应义斌. 水果按表面颜色分级的方法[J]. 浙江大学学报: 工学版, 2009, 43(5): 869-871.
[2] 郭丹, 韩英群, 郝义. 秋富红苹果冷藏期及货架期生理品质变化[J]. 食品与机械, 2015, 31(4): 126-129.
[3] 刘璇, 王沛, 毕金峰, 等. 基于层次分析法的晚熟品种苹果脆片品质评价[J]. 食品与机械, 2012, 28(5): 46-50.
[4] 殷勇, 陶凯, 于慧春. 基于机器视觉的苹果分级中特征参量选择方法[J]. 农业机械学报, 2012, 43(6): 118-127.
[5] 李先锋, 朱伟兴, 花小朋, 等. 基于D-S证据理论的决策级多特征融合苹果分级方法[J]. 农业机械学报, 2011, 42(6): 188-192.
[6] 赵茂程, 侯文军. 基于神经网络的苹果自动分级方法[J]. 南京林业大学学报: 自然科学版, 2009, 33(1): 136-138.
[7] 姚立健, 边起, 雷良育, 等. 基于BP神经网络的水果分级研究[J]. 浙江农业学报, 2012, 24(5): 926-930.
[8] 黄星奕, 魏海丽, 赵杰文. 实时在线检测苹果果形的一种计算方法[J]. 食品与机械, 2006, 22(1): 27-29.
[9] XIE Feng-yun, HU You-min, WU Bo, et al. A generalized interval probability-based optimization method for training generalized hidden Markov model[J]. Signal Processing, 2014, 94(1): 319-329.
[10] 周萧, 王岩. 基于Hu不变矩的叶片图像识别技术的研究[J]. 伺服控制, 2011(6): 70-72.
[11] XIE Feng-yun, HU You-min, WANG Yan, et al. A generalized Markov chain model based on generalized interval probability[J]. Science China Technological Sciences, 2013, 56(9): 2 132-2 136.