Sugarcane stem nodes based on the maximum value points of the vertical projection function

Chen, Jiqing; Qiang, Hu; Xu, Guanwen; Wu, Jiahua; Liu, Xu; Mo, Rongxian; Huang, Renzhi

doi:10.1590/0103-8478cr20190797

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CROP PRODUCTION • Cienc. Rural 50 (12) • 2020 • https://doi.org/10.1590/0103-8478cr20190797 copy

Sugarcane stem nodes based on the maximum value points of the vertical projection function

Identificação de nós de tronco de cana-de-açúcar com base nos pontos de valor extremos da função de projeção vertical

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT:

In order to solve the problem that the stem nodes are difficult to identify in the process of sugarcane seed automatic cutting, a method of identifying the stem nodes of sugarcane based on the extreme points of vertical projection function is proposed in this paper. Firstly, in order to reduce the influence of light on image processing, the RGB color image is converted to HSI color image, and the S component image of the HSI color space is extracted as a research object. Then, the S component image is binarized by the Otsu method, the hole of the binary image is filled by morphology closing algorithm, and the sugarcane and the background are initially separated by the horizontal projection map of the binary image. Finally, the position of sugarcane stem is preliminarily determined by continuously taking the derivative of the vertical projection function of the binary image, and the sum of the local pixel value of the suspicious pixel column is compared to further determine the sugarcane stem node. The experimental results showed that the recognition rate of single stem node is 100%, and the standard deviation is less than 1.1 mm. The accuracy of simultaneous identification of double stem nodes is 98%, and the standard deviation is less than 1.7 mm. The accuracy of simultaneous identification of the three stem nodes is 95%, and the standard deviation is less than 2.2 mm. Compared with the other methods introduced in this paper, the proposed method has higher recognition and accuracy.

Keywords:
automatic cutting; sugarcane stem node; vertical projection function; maximum value points; summation of local pixel values

Universidade Federal de Santa Maria Universidade Federal de Santa Maria, Centro de Ciências Rurais , 97105-900 Santa Maria RS Brazil , Tel.: +55 55 3220-8698 , Fax: +55 55 3220-8695 - Santa Maria - RS - Brazil
E-mail: cienciarural@mail.ufsm.br

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[1] E-mail: cjq_gz@163.com. ^*Corresponding autor

Parameter	Value
Model	MER-132-30U3M/C
Frame rate	30fps
Maximum resolution	1292 x 964
Sensor type	1/3" CCD
Data interface	Mini USB3.0
Power consumption	<2W @5V
Mechanical dimension (L x W x H)	29 mm x 29 mm x 29 mm
Working temperature	0° C ~ +45 °C
Working humidity	10% ~ 80%
Weight	57g

x	y	x	y	x	y	x	y	x	y	x	y	x	y	x	y
8	105	98	84	142	103	174	106	232	87	339	108	428	104	518	103
12	108	100	84	146	108	176	107	236	84	344	106	430	104	529	105
14	109	102	85	148	107	182	106	243	102	346	106	436	104	554	107
17	109	109	89	150	107	184	107	258	90	353	106	438	104	558	106
26	108	114	97	152	106	186	107	260	90	382	105	440	104	578	110
34	109	116	98	154	103	188	107	274	109	386	107	442	104	580	110
57	115	118	95	156	100	190	107	280	109	397	108	444	104	603	110
64	114	120	96	158	100	199	103	287	109	399	108	456	105	612	110
70	99	122	95	160	103	201	103	304	116	404	108	468	108	616	113
76	93	124	96	162	102	211	97	310	115	408	107	476	107	618	110
79	92	126	94	164	103	214	96	318	111	414	107	489	104	620	111
86	88	130	105	166	106	218	97	320	110	420	105	494	104	622	109
88	89	132	104	168	103	222	96	323	108	422	105	498	106
90	88	138	104	170	104	226	96	330	108	424	104	501	106
96	92	140	104	172	105	230	92	335	107	426	104	514	105

x	y	x	y	x	y	x	y	x	y	x	y
3	109	21	98	32	108	49	107	76	108	108	107
7	115	23	96	39	103	57	97	82	108	112	113
13	89	25	96	42	106	63	102	99	108	114	111
15	92	27	105	47	107	69	116	103	106

x	y	x	y	x	y	x	y	x	y	x	y
2	115	5	98	9	108	12	107	16	116	22	113

x	s	x	s	x	s	x	s	x	s	x	s	x	s
12	2208	57	2330	304	2321	323	2273	339	2221	399	2252	468	2222
26	2269	146	2159	310	2378	330	2237	397	2252	404	2252	606	2325

x	y	x	y	x	y	x	y	x	y	x	y	x	y	x	y
8	105	98	84	142	103	174	106	232	87	339	108	428	104	518	103
12	108	100	84	146	108	176	107	236	84	344	106	430	104	529	105
14	109	102	85	148	107	182	106	243	102	346	106	436	104	554	107
17	109	109	89	150	107	184	107	258	90	353	106	438	104	558	106
26	108	114	97	152	106	186	107	260	90	382	105	440	104	578	110
34	109	116	98	154	103	188	107	274	109	386	107	442	104	580	110
57	115	118	95	156	100	190	107	280	109	397	108	444	104	603	110
64	114	120	96	158	100	199	103	287	109	399	108	456	105	612	110
70	99	122	95	160	103	201	103	304	116	404	108	468	108	616	113
76	93	124	96	162	102	211	97	310	115	408	107	476	107	618	110
79	92	126	94	164	103	214	96	318	111	414	107	489	104	620	111
86	88	130	105	166	106	218	97	320	110	420	105	494	104	622	109
88	89	132	104	168	103	222	96	323	108	422	105	498	106
90	88	138	104	170	104	226	96	330	108	424	104	501	106
96	92	140	104	172	105	230	92	335	107	426	104	514	105

x	y	x	y	x	y	x	y	x	y	x	y
3	109	21	98	32	108	49	107	76	108	108	107
7	115	23	96	39	103	57	97	82	108	112	113
13	89	25	96	42	106	63	102	99	108	114	111
15	92	27	105	47	107	69	116	103	106

Algorithm		K	P	R (%)	A (s)	M (mm)	S (mm)
SHI		25	292	92	1.96	∕	∕
Moshashai		∕	∕	97.92	0.5	2.08	2.97
Huang		1	99	99	0.634	∕	∕
Pothula		9	263	96.6	∕	∕	∕
The proposed	single	0	100	100	0.19	0.45	1.093
	double	4	196	98	0.22	1.161	1.676
	three	15	285	95	0.30	1.197	2.123

x	y	x	y	x	y	x	y	x	y	x	y	x	y	x	y
8	105	98	84	142	103	174	106	232	87	339	108	428	104	518	103
12	108	100	84	146	108	176	107	236	84	344	106	430	104	529	105
14	109	102	85	148	107	182	106	243	102	346	106	436	104	554	107
17	109	109	89	150	107	184	107	258	90	353	106	438	104	558	106
26	108	114	97	152	106	186	107	260	90	382	105	440	104	578	110
34	109	116	98	154	103	188	107	274	109	386	107	442	104	580	110
57	115	118	95	156	100	190	107	280	109	397	108	444	104	603	110
64	114	120	96	158	100	199	103	287	109	399	108	456	105	612	110
70	99	122	95	160	103	201	103	304	116	404	108	468	108	616	113
76	93	124	96	162	102	211	97	310	115	408	107	476	107	618	110
79	92	126	94	164	103	214	96	318	111	414	107	489	104	620	111
86	88	130	105	166	106	218	97	320	110	420	105	494	104	622	109
88	89	132	104	168	103	222	96	323	108	422	105	498	106
90	88	138	104	170	104	226	96	330	108	424	104	501	106
96	92	140	104	172	105	230	92	335	107	426	104	514	105

x	y	x	y	x	y	x	y	x	y	x	y
3	109	21	98	32	108	49	107	76	108	108	107
7	115	23	96	39	103	57	97	82	108	112	113
13	89	25	96	42	106	63	102	99	108	114	111
15	92	27	105	47	107	69	116	103	106

x	y	x	y	x	y	x	y	x	y	x	y	x	y	x	y
8	105	98	84	142	103	174	106	232	87	339	108	428	104	518	103
12	108	100	84	146	108	176	107	236	84	344	106	430	104	529	105
14	109	102	85	148	107	182	106	243	102	346	106	436	104	554	107
17	109	109	89	150	107	184	107	258	90	353	106	438	104	558	106
26	108	114	97	152	106	186	107	260	90	382	105	440	104	578	110
34	109	116	98	154	103	188	107	274	109	386	107	442	104	580	110
57	115	118	95	156	100	190	107	280	109	397	108	444	104	603	110
64	114	120	96	158	100	199	103	287	109	399	108	456	105	612	110
70	99	122	95	160	103	201	103	304	116	404	108	468	108	616	113
76	93	124	96	162	102	211	97	310	115	408	107	476	107	618	110
79	92	126	94	164	103	214	96	318	111	414	107	489	104	620	111
86	88	130	105	166	106	218	97	320	110	420	105	494	104	622	109
88	89	132	104	168	103	222	96	323	108	422	105	498	106
90	88	138	104	170	104	226	96	330	108	424	104	501	106
96	92	140	104	172	105	230	92	335	107	426	104	514	105

x	y	x	y	x	y	x	y	x	y	x	y
3	109	21	98	32	108	49	107	76	108	108	107
7	115	23	96	39	103	57	97	82	108	112	113
13	89	25	96	42	106	63	102	99	108	114	111
15	92	27	105	47	107	69	116	103	106