Method for detecting field navigation line after ridge sealing of crops

Patent metadata

Field	Value
Publication number	US-11676376-B2
Application number	US-202017780029-A
Country	US
Kind code	B2
Filing date	Sep 15, 2020
Priority date	Sep 4, 2020
Publication date	Jun 13, 2023
Grant date	Jun 13, 2023

Abstract

A method for detecting a field navigation line after ridge sealing of crops includes the following steps. A field crop image is acquired. Image color space transformation, image binaryzation, longitudinal integration, neighborhood setting and region integration calculation are sequentially performed on the field crop image to obtain a crop row image. Detections of an initial middle ridge, a left ridge and a right ridge are performed on the crop row image to obtain center lines of the initial middle ridge, left ridge and right ridge. Center lines of a left (right) crop row are established by using an area 1 between the center lines of the left (right) ridge and the initial middle ridge. A center line model of a middle ridge is established by using an area 0 between the center lines of the left and right crop rows, namely a navigation line of a field operation machine.

First claim

What is claimed is:

1. A method for detecting a field navigation line after a ridge sealing of crops, characterized in that the method comprises steps as follows:
1) performing crop image acquisition, wherein a camera is used to acquire a field crop image, recorded as an original image S 1 ;
2) performing image color space transformation, wherein the original image S 1 is converted to HSI color space to obtain an HSI image S 2 ;
3) performing image binarization to obtain a binary image S 3 ;
4) processing longitudinal integration of the binary image S 3 to obtain a longitudinal integral image S 4 ;
5) performing neighborhood setting,
wherein a neighborhood of a current pixel is set, the neighborhood is 1/48 of an image width of the original image S 1 , a 3-row two-dimensional matrix R is used to represent the neighborhood, a column in the two-dimensional matrix R represents a column in the neighborhood, each element of a first row in the two-dimensional matrix R represents a column offset of each column in the neighborhood relative to the current pixel, each element of a second row represents an abscissa offset of a start row of each column in the neighborhood, and each element of a third row represents an abscissa offset of an end row of each column in the neighborhood;
6) performing region integration calculation,
wherein a blank image having a size the same as that of the longitudinal integral image S 4 is constructed as a region integration image S 5 , and each pixel is traversed on the longitudinal integral image S 4 , which is processed in the way as follows: when traversing, current pixel coordinates are marked as (x, y), an accumulator C is set, and an initial value of the accumulator C is set to be 0; when traversing each column of the two-dimensional matrix R and traversing the two-dimensional matrix R, elements of the first row to the third row of a current j-th column are R 1j , R 2j , and R 3j , a difference is obtained by subtracting a pixel value of a pixel with coordinates (x+R 3j −1, y+R 1j ) from a pixel value of a pixel with coordinates (x+R 3j , y+R 1j ) on the longitudinal integral image S 4 , the difference is accumulated into the accumulator C, after traversing the two-dimensional matrix R is completed, a value in the accumulator C is taken as a regional integral value M of the current pixel, the regional integral value M is assigned to the pixel having coordinates the same as those of the current pixel in the region integration image S 5 , and after traversing each pixel of the longitudinal integral image S 4 is completed, the region integration image S 5 is obtained;
7) performing detections of crop rows, wherein each row is traversed in the region integration image S 5 , an average value of the regional integral value M of all pixels in each row is calculated, a pixel whose regional integral value M is greater than the average value is set to be 1, the remaining pixels are set to be 0, and a crop row image S 6 is obtained;
8) performing detections of an initial middle ridge, a left ridge, and a right ridge;
9) performing detections of left crop row and right crop row;
10) performing detection of a middle ridge.

2. The method for detecting the field navigation line after the ridge sealing of the crops according to claim 1 , wherein the step 3) specifically comprises: setting a pixel value of the pixel whose hue component value H is between 0.2 and 0.583 in the HSI image S 2 to 1, and setting a pixel value of remaining pixels to 0 to obtain the binary image S 3 .

3. The method for detecting the field navigation line after the ridge sealing of the crops according to claim 1 , wherein the step 4) specifically comprises: duplicating the binary image S 3 as the longitudinal integral image S 4 ; traversing each column on the longitudinal integral image S 4 ; in each column, traversing each pixel downward from a pixel of the second row; when traversing, pixel values of pixels of the previous row are added; and covering a result with a pixel value of the current pixel, so as to obtain the longitudinal integral image S 4 .

4. The method for detecting the field navigation line after the ridge sealing of the crops according to claim 1 , wherein the step 8) specifically comprises:
8.1) dividing the crop row image S 6 into N crop row sub-images S 7 having a width the same as a width of the crop row image S 6 and a height 1/N of a height of the crop row image S 6 ;
8.2) taking an i-th crop row sub-image S 7 , and calculating a longitudinal projection vector S 8 of the i-th crop row sub-image S 7 ;
8.3) performing detection of the left boundary of the initial middle ridge, wherein an initial middle ridge start detection template ML 0 is constructed, the initial middle ridge start detection template ML 0 is a vector whose length is ⅙ of a width of the original image S 1 , a first half is 1, a second half is −1, the longitudinal projection vector S 8 is convolved with the initial middle ridge start detection template ML 0 , and a column number of a position of a point with a maximum convolution value is taken as an initial middle ridge left boundary p0L0 i of the i-th crop row sub-image S 7 ;
8.4) performing detection of a right boundary of the initial middle ridge, wherein an initial middle ridge termination detection template MR 0 is constructed, the initial middle ridge termination detection template MR 0 is a vector whose length is ⅙ of the width of the original image S 1 , a first half is −1, a second half is 1, the longitudinal projection vector S 8 is convolved with the initial middle ridge termination detection template MR 0 , and a column number of a position of a point with a maximum convolution value is taken as an initial middle ridge right boundary p0R0 i of the i-th crop row sub-image S 7 ;
8.5) calculating an initial middle ridge center p0M0 i of the i-th crop row sub-image S 7 by a formula as follows: p0M0 i =(p0L0 i +p0R0 i )/2;
8.6) performing detection of a left boundary of an initial left row, wherein an initial left row start detection template MR 1 is constructed, the initial left row start detection template MR 1 is a vector whose length is ½ of a length of the initial middle ridge termination detection template MR 0 , a first half is −1, a second half is 1, the initial left row start detection template MR 1 is used to be convolved with data of the longitudinal projection vector S 8 on the left side of the initial middle ridge left boundary p0L0 i , and a column number of a position of a point with the maximum convolution value is taken as an initial left row left boundary CL0 i of the i-th crop row sub-image S 7 ;
8.7) performing detection of a right boundary of an initial right row, wherein an initial right row termination detection template ML 1 is constructed, wherein the initial right row termination detection template ML 1 is a vector whose length is ½ of a length of the initial middle ridge start detection template ML 0 , a first half is 1, a second half is −1, the initial right row termination detection template ML 1 is used to be convolved with data of the longitudinal projection vector S 8 on the right side of the initial middle ridge right boundary p0R0 i , and a column number of a position of a point with the maximum convolution value is taken as an initial right row right boundary CR0 i of the i-th crop row sub-image S 7 ;
8.8) performing estimation of a center point of the left ridge, wherein an initial left row horizontal center column CLM0 i of the i-th crop row sub-image S 7 is calculated by the following formula: CLM0 i =(CL0 i +p0L0 i )/2, and then a column pLM0 i where the center point of the left ridge of the i-th crop row sub-image S 7 is located is calculated by the following formula: pLM0 i =2×CLM0 i −p0M0 i ;
8.9) performing estimation of a

Assignees

• Univ Zhejiang

Inventors

• Rao Xiuqin
• Lin Yangyang
• Zhang Yanning
• Zhang Xiaomin
• Ying Yibin
• Yang Haitao
• Jiang Haiyi
• Zhu Yihang

Classifications

• G01C21/00 Primary

  Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 (measuring distance traversed on the ground by a vehicle G01C22/00; control of position, course, altitude or attitude of vehicles G05D1/00; traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968) · CPC title

• G06V20/188 Primary

  Vegetation · CPC title

• G01C21/20

  Instruments for performing navigational calculations (G01C21/24, G01C21/26 take precedence) · CPC title

• G06V10/23

  based on positionally close patterns or neighbourhood relationships · CPC title

• G06V10/56

  relating to colour · CPC title