Wheat variety recognition method based on same position segmentation of transmitted light and reflected light images

doi:10.3969/j.issn.1004-1524.2022.03.20

Acta Agriculturae Zhejiangensis ›› 2022, Vol. 34 ›› Issue (3): 590-598.DOI: 10.3969/j.issn.1004-1524.2022.03.20

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Wheat variety recognition method based on same position segmentation of transmitted light and reflected light images

YAN Ning¹^,²(), ZHANG Han²^,^*(), DONG Hongtu³, KANG Kai³, LUO Bin²

1. School of Mechanical Engineering, North University of China, Taiyuan 030051, China
2. Beijing Research Center for Intelligent Agricultural Equipment, Beijing 100094, China
3. Beijing Agricultural Information Technology Research Center, Beijing 100094, China

Received:2021-07-19 Online:2022-03-25 Published:2022-03-30
Contact: ZHANG Han

Abstract

Abstract:

A segmentation method of embryo and endosperm image based on transmitted light and reflected light at the same position of wheat seeds was proposed in order to improve the recognition accuracy of wheat varieties. In this paper, according to the characteristics of great difference in transmissibility between embryo and endosperm of wheat seed, color feature information was extracted from reflected light images and transmitted light images for modeling and analysis, the influence of transmission light characteristics and color characteristics of seed embryo and endosperm on wheat seed variety recognition were studied. Taking the four varieties of seeds of Jimai 22, Jimai 44, Jingmai 9, and Jingmai 11 as the materials, the color characteristic parameters of the seeds were obtained by using the HALCON machine vision software, and through partial least squares discriminant analysis (PLS-DA) method to establish a classification model. The results showed that after the transmission light image was used to assist the reflected light image segmentation, more seed color parameter information was fused, so that the accuracy of the four varieties of wheat seed recognition was improved. The correct rate of hybrid recognition between Jimai and Jingmai had increased from 95% of the color characteristics of seed reflected light to more than 99% of the color characteristics of transmitted light, embryo and endosperm. The hybrid recognition accuracy rate of Jimai 22 and Jimai 44 increased from 73.28% to 84.60%, and the hybrid recognition accuracy rate of Jingmai 9 and Jingmai 11 increased from 74.15% to 83.73%. The further fusion analysis of the color features contained in the image of seed embryo and endosperm through the transmitted light features can effectively improve the accuracy of wheat variety recognition.

Key words: machine vision, wheat, species identification, transmitted light, embryo, endosperm, color features

CLC Number:

TP391.4

YAN Ning, ZHANG Han, DONG Hongtu, KANG Kai, LUO Bin. Wheat variety recognition method based on same position segmentation of transmitted light and reflected light images[J]. Acta Agriculturae Zhejiangensis, 2022, 34(3): 590-598.

Figures/Tables 9

References 30

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特征分类 Feature classification	提取特征 Extract features	分选区间 Sorting interval	京麦9 Jingmai 9	京麦11 Jingmai 11	济麦22 Jimai 22	济麦44 Jimai 44	准确率 Accuracy/%
整粒Seeds	B_tm	<84.215	3	4	49	47	94.5
		≥84.215	47	46	1	3
	R_td	<35.09	2	4	49	43	93.0
		≥35.09	48	46	1	7
	G_td	<33.395	4	4	49	43	92.0
		≥33.395	46	46	1	7
	V_td	<35.22	2	4	49	43	93.0
		≥35.22	48	46	1	7
胚部Seed embryo	B_tm	<59.365	3	2	46	44	92.5
		≥59.365	47	48	4	6
胚乳部Seed endosperm	B_tm	<89.78	4	3	49	46	94.0
		≥89.78	46	47	1	4
	R_td	<30.405	5	5	48	43	90.5
		≥30.405	45	45	2	7
	V_td	<30.52	5	5	48	43	90.5
		≥30.52	45	45	2	7

特征分类 Feature classification	提取特征 Extract features	分选区间 Sorting interval	京麦9 Jingmai 9	京麦11 Jingmai 11	济麦22 Jimai 22	济麦44 Jimai 44	准确率 Accuracy/%
整粒Seeds	B_tm	<84.215	3	4	49	47	94.5
		≥84.215	47	46	1	3
	R_td	<35.09	2	4	49	43	93.0
		≥35.09	48	46	1	7
	G_td	<33.395	4	4	49	43	92.0
		≥33.395	46	46	1	7
	V_td	<35.22	2	4	49	43	93.0
		≥35.22	48	46	1	7
胚部Seed embryo	B_tm	<59.365	3	2	46	44	92.5
		≥59.365	47	48	4	6
胚乳部Seed endosperm	B_tm	<89.78	4	3	49	46	94.0
		≥89.78	46	47	1	4
	R_td	<30.405	5	5	48	43	90.5
		≥30.405	45	45	2	7
	V_td	<30.52	5	5	48	43	90.5
		≥30.52	45	45	2	7

二分类小麦品种 Binary classification of wheat varieties	整粒透射光 Seeds transmitted light	整粒反射光 Seeds reflected light	整粒全光 Seeds full light	分割透射光 Transmitted light after seeds segmentation	分割反射光 Reflected light after seeds segmentation	分割全光 Full light after seeds segmentation	全部特征 All features
京麦9、济麦22	98.88	95.50	99.43	99.43	96.38	99.60	99.98
Jingmai 9、Jimai 22
京麦9、济麦44	98.90	95.55	99.10	99.45	97.63	99.53	99.90
Jingmai 9、Jimai 44
京麦11、济麦22	98.68	95.25	99.00	99.10	95.18	99.18	99.58
Jingmai 11、Jimai 22
京麦11、济麦44	98.43	95.08	99.10	99.33	94.53	99.60	99.68
Jingmai 11、Jimai 44
京麦组、济麦组	99.38	95.78	99.69	99.61	97.58	99.78	99.84
Jingmai Group、Jimai Group
济麦22、济麦44	69.48	73.28	83.00	81.60	76.88	83.75	84.60
Jimai 22、Jimai 44
京麦9、京麦11	59.98	74.15	75.28	72.45	76.20	81.83	83.73
Jingmai 9、Jingmai 11

二分类小麦品种 Binary classification of wheat varieties	整粒透射光 Seeds transmitted light	整粒反射光 Seeds reflected light	整粒全光 Seeds full light	分割透射光 Transmitted light after seeds segmentation	分割反射光 Reflected light after seeds segmentation	分割全光 Full light after seeds segmentation	全部特征 All features
京麦9、济麦22	98.88	95.50	99.43	99.43	96.38	99.60	99.98
Jingmai 9、Jimai 22
京麦9、济麦44	98.90	95.55	99.10	99.45	97.63	99.53	99.90
Jingmai 9、Jimai 44
京麦11、济麦22	98.68	95.25	99.00	99.10	95.18	99.18	99.58
Jingmai 11、Jimai 22
京麦11、济麦44	98.43	95.08	99.10	99.33	94.53	99.60	99.68
Jingmai 11、Jimai 44
京麦组、济麦组	99.38	95.78	99.69	99.61	97.58	99.78	99.84
Jingmai Group、Jimai Group
济麦22、济麦44	69.48	73.28	83.00	81.60	76.88	83.75	84.60
Jimai 22、Jimai 44
京麦9、京麦11	59.98	74.15	75.28	72.45	76.20	81.83	83.73
Jingmai 9、Jingmai 11

Wheat variety recognition method based on same position segmentation of transmitted light and reflected light images

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